ai - data scientist · a data scientist needs to have excellent analytical skills, attention to...
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Qualification Pack
AI - Data Scientist
Electives: Model Risk Assessment/ Model Business Performance/ Visualizations
QP Code: SSC/Q8104
NSQF Level: 7
IT-ITeS Sector Skill Council || IT-ITeS Sector Skill Council, NASSCOM,Plot No - 7, 8, 9 & 10,3rd Floor,
Sector 126, Noida Uttar Pradesh - 201303
IT-ITeS Sector Skill Council 1
Qualification Pack
Contents
SSC/Q8104: AI - Data Scientist ............................................................................................................... 3
Brief Job Description ........................................................................................................................ 3 Applicable National Occupational Standards (NOS) ................................................................................ 3
Compulsory NOS ............................................................................................................................. 3 Elective 1: Model Risk Assessment .................................................................................................. 3 Elective 2: Model Business Performance ......................................................................................... 3 Elective 3: Visualizations .................................................................................................................. 4 Qualification Pack (QP) Parameters ................................................................................................. 4
SSC/N8101: Import Data as per specifications ........................................................................................ 5 SSC/N8102: Pre process data as per specifications ................................................................................ 9 SSC/N8103: Perform exploratory data analysis as per specifications .................................................... 13 SSC/N8105: Apply pre-designed algorithmic models to specified use cases ......................................... 17 SSC/N8104: Perform research and design of algorithmic models ......................................................... 21 SSC/N9001: Manage your work to meet requirements .......................................................................... 27 SSC/N9002: Work effectively with colleagues ....................................................................................... 31 SSC/N9004: Provide data/information in standard formats .................................................................... 35 SSC/N9006: Build and Maintain relationships in a Workplace ............................................................... 39 SSC/N9007: Build and Maintain client satisfaction ................................................................................ 43 SSC/N9010: Convince others to take appropriate action in different situations ...................................... 47 SSC/N9014: Maintain an inclusive, environmentally sustainable workplace……………………………... 50 SSC/N8106: Evaluate risk of deploying algorithmic models ................................................................... 54 SSC/N8107: Evaluate business performance of algorithmic models ..................................................... 58 SSC/N8108: Define business outcomes and create visualizations from results of the analysis ............. 62 Assessment Guidelines and Weightage ................................................................................................ 66
Assessment Guidelines .................................................................................................................. 66 Assessment Weightage .................................................................................................................. 66
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Qualification Pack
SSC/Q8104: AI - Data Scientist
Brief Job Description
Individuals at this job are responsible for performing different elements of data science such as importing
and pre processing data, performing exploratory analysis, research and design of algorithmic models.
Personal Attributes
A data scientist needs to have excellent analytical skills, attention to detail, critical thinking and problem
solving ability. S/he needs to have strong communication skills and a superior understanding of the
business to work with stakeholders and decision makers across the organization.
Applicable National Occupational Standards (NOS)
Compulsory NOS:
1. SSC/N8101: Import Data as per specifications
2. SSC/N8102: Preprocess data as per specifications
3. SSC/N8103: Perform exploratory data analysis as per specifications
4. SSC/N8105: Apply pre-designed algorithmic models to specified use cases
5. SSC/N8104: Perform research and design of algorithmic models
6. SSC/N9001: Manage your work to meet requirements
7. SSC/N9002: Work effectively with colleagues
8. SSC/N9004: Provide data/information in standard formats
9. SSC/N9006: Build and Maintain relationships in a Workplace
10. SSC/N9007: Build and Maintain client satisfaction
11. SSC/N9010: Convince others to take appropriate action in different situations
12. SSC/N9014: Maintain an inclusive, environmentally sustainable workplace Electives (mandatory to select at least one):
Elective 1: Model Risk Assessment
The individual would evaluate risks to model and develop mitigation measures
1. SSC/N8106: Evaluate risk of deploying algorithmic models
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Qualification Pack
Elective 2: Model Business Performance
The individual would evaluate performance of the model at meeting business outcomes
1. SSC/N8107: Evaluate business performance of algorithmic models
Elective 3: Visualizations
The individual would define business outcomes based on the results of the analysis and create
visualizations to present said outcomes to relevant stakeholders
1. SSC/N8108: Define business outcomes and create visualizations from results of the analysis
Qualification Pack (QP) Parameters
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence and Big Data Analytics
Secondary Occupation
Country India
NSQF Level 7
Aligned to NCO/ISCO/ISIC NCO-2015/NIL
Code
Minimum Educational Graduate
Qualification & (Engineering/Technology/Statistics/Mathematics/Computer
Experience Science) with 5-10 Years of experience Recommended
Minimum Level of
12th Class Education for Training in
School
Pre-Requisite License or NA
Training
Minimum Job Entry Age 21 Years
Last Reviewed On 31/03/2020
Next Review Date 31/03/2025
NSQC Approval Date NA
Version 2.0
IT-ITeS Sector Skill Council 4
Qualification Pack
SSC/N8101: Import Data as per specifications
Description
This unit is about using a variety of techniques to import data into datasets or data frames.
Scope
This unit/task covers the following:
• Define data type and sources
• Acquire the data
Elements and Performance Criteria
Define data type and sources To be competent, the user/individual on the job must be able to:
PC1. identify the objective of the analysis PC2. define the type of data to be imported PC3. define the volume of data to be imported PC4. define the key variables to be imported PC5. identify suitable sources for the data Acquire the data To be competent, the user/individual on the job must be able to:
PC6. perform operations to acquire the data and store it in datasets or data frames
PC7. populate metadata for the imported data PC8. validate imported data using appropriate tools & processes PC9. validate the desired output with the relevant stakeholders within the organization, if required
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the purpose and aims of the statistical analysis being undertaken
KU2. organizational policies, procedures and guidelines which relate to importing and sharing data KU3. different data sources and how to access documents and information from data sources KU4. who to consult when importing data KU5. the range of standard templates and tools available and how to use them KU6. the difference between various types of data. For example, enterprise vs consumer data
qualitative vs quantitative data processed vs unprocessed data KU7. statistical analysis Softwares, packages, libraries and tools that can be used to import &
validate data such as R or Pandas KU8. functions to read data from various file formats and import it to a dataset or data frame KU9. the metadata associated with imported data and how to populate it
IT-ITeS Sector Skill Council 5
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KU10. how to store and retrieve information
KU11. various operating systems such as linux, ubuntu, or windows
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. follow instructions, guidelines, procedures, rules and service level agreements
GS2. evaluate impact analysis of the various actions performed and disseminate relevant
information to others GS3. check the work completion without errors
IT-ITeS Sector Skill Council 6
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Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define data type and sources 20 35 - -
PC1. identify the objective of the analysis 5 5 - -
PC2. define the type of data to be imported 2 5 - -
PC3. define the volume of data to be 3 5 - -
imported
PC4. define the key variables to be 5 10 - -
imported
PC5. identify suitable sources for the data 5 10 - -
Acquire the data 10 35 - -
PC6. perform operations to acquire the data 5 15 - -
and store it in datasets or data frames
PC7. populate metadata for the imported 5 10 - -
data
PC8. validate imported data using - 5 - -
appropriate tools & processes
PC9. validate the desired output with the
- 5 - - relevant stakeholders within the
organization, if required
NOS Total 30 70 - -
IT-ITeS Sector Skill Council 7
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National Occupational Standards (NOS) Parameters
NOS Code SSC/N8101
NOS Name Import Data as per specifications
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 6
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 8
Qualification Pack
SSC/N8102: Pre-process data as per specifications
Description
This unit is about using a variety of techniques to pre-process data i.e. clean and transform the data.
Scope
This unit/task covers the following:
• Define the dataset
• Perform data pre-processing operations
Elements and Performance Criteria
Define the dataset To be competent, the user/individual on the job must be able to:
PC1. define the format and structure for the dataset PC2. define indexes and organize variables as per the defined format PC3. identify data types for each variable of the dataset Perform data pre-processing operations To be competent, the user/individual on the job must be able to:
PC4. identify and fix missing values in each variable of the dataset PC5. identify and fix incorrect data types in each variable of the dataset PC6. sort the data and create subsets of the data as required PC7. perform operations to transform data types of variables as required PC8. identify and deal with data redundancy by normalizing the dataset PC9. validate preprocessed data using appropriate tools and processes
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the purpose and aims of the statistical analysis being undertaken
KU2. organizational policies, procedures and guidelines which relate to pre-processing and sharing data
KU3. data sources and how to access documents and information from data sources KU4. whom to consult while pre-processing data KU5. the range of standard templates and tools available and how to use them KU6. the difference between various types of data. For example, qualitative vs quantitative data
processed vs unprocessed data discrete vs continuous data KU7. statistical analysis software, packages, libraries and tools that can be used to pre-
process data such as R or Pandas KU8. functions to identify and remove missing values
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KU9. functions to identify and transform data types of variables such as integer, float, character KU10. methodological approaches for normalizing the dataset such as standard score, feature
scaling, etc. KU11. data formats and structures KU12. identification of anomalies in data KU13. various databases and operating systems
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. evaluate impact analysis of the various actions performed and disseminate relevant
information to others GS2. analyze data and understand its implications on business
GS3. check the work completion without errors
IT-ITeS Sector Skill Council 10
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Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define the dataset 5 15 - -
PC1. define the format and structure for the - 5 - -
dataset
PC2. define indexes and organize variables 2 3 - -
as per the defined format
PC3. identify data types for each variable of 3 7 - -
the dataset
Perform data pre-processing operations 25 55 - -
PC4. identify and fix missing values in each 5 10 - -
variable of the dataset
PC5. identify and fix incorrect data types in 5 10 - -
each variable of the dataset
PC6. sort the data and create subsets of the 5 10 - -
data as required
PC7. perform operations to transform data 5 10 - -
types of variables as required
PC8. identify and deal with data redundancy 5 10 - -
by normalizing the dataset
PC9. validate pre-processed data using - 5 - -
appropriate tools and processes
NOS Total 30 70 - -
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National Occupational Standards (NOS) Parameters
NOS Code SSC/N8102
NOS Name Preprocess data as per specifications
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 6
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 12
Qualification Pack
SSC/N8103: Perform exploratory data analysis as per specifications
Description
This unit is about using a variety of techniques to perform exploratory analysis to describe and summarize
data for internal and external clients
Scope
This unit/task covers the following:
• Define the dataset
• Summarize and optimize the dataset
Elements and Performance Criteria
Define the dataset To be competent, the user/individual on the job must be able to:
PC1. identify the data types for each variable of the dataset
PC2. identify the key variables required for modelling or analysis
Summarize and optimize the dataset To be competent, the user/individual on the job must be able to:
PC3. use statistical techniques to summarize the key variables in the dataset
PC4. describe summary statistics for key variables using graphical formats PC5. perform dimension reduction to optimize the variables in the dataset, if required
PC6. define the correlation factors using clustering and other techniques PC7. validate data using appropriate tools and processes
PC8. repeat the analysis iteratively to arrive at optimal results PC9. validate the final output in consultation with the relevant stakeholders
PC10. gain inferences from the final output of the data analysis PC11. develop a hypothesis model to explain the discovered inferences PC12. evaluate the results of the analysis and define business outcomes PC13. define prescriptive actions based on the defined business outcomes
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the purpose and aims of the statistical analysis being undertaken
KU2. organizational policies, procedures and guidelines which relate to performing explanatory
analysis KU3. data sources and how to access documents and information from data sources KU4. organizational policies and procedures for sharing data KU5. whom to consult when performing explanatory analysis
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KU6. the range of standard templates and tools available and how to use them
KU7. the difference between various types of data. For example, qualitative vs quantitative data
processed vs unprocessed data discrete vs continuous data KU8. statistical analysis software, packages, libraries and tools that can be used to pre-process
and summarize data such as R, NumPy, Statistical models, or Pandas
KU9. functions to summarize variables across different data types such as integer, float, or
character KU10. graphical formats to describe summary statistics KU11. methodological approaches for dimension reduction such as PCA, LDA, or NMF KU12. methodological approaches for defining correlations between variables such as the scatter
diagram method, correlation coefficients, method of least squares KU13. multivariate visualizations, for mapping and understanding interactions between different
fields in the data KU14. The inferences from analysed data and explain it using a hypothesis model KU15. types of prescriptive actions KU16. identification of anomalies in data KU17. various operating systems such as linux, ubuntu, or windows
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. evaluate impact analysis of the various actions performed and disseminate relevant
information to others GS2. analyze data and understand its implications on business
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Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define the dataset 5 8 - -
PC1. identify the data types for each variable 2 3 - -
of the dataset
PC2. identify the key variables required for 3 5 - -
modelling or analysis
Summarize and optimize the dataset 25 62 - -
PC3. use statistical techniques to summarize 5 10 - -
the key variables in the dataset
PC4. describe summary statistics for key 2 6 - -
variables using graphical formats
PC5. perform dimension reduction to optimize 3 5 - -
the variables in the dataset, if required
PC6. define the correlation factors using 3 5 - -
clustering and other techniques
PC7. validate data using appropriate tools and - 5 - -
processes
PC8. repeat the analysis iteratively to arrive at 2 6 - -
optimal results
PC9. validate the final output in consultation - 5 - -
with the relevant stakeholders
PC10. gain inferences from the final output of 2 5 - -
the data analysis
PC11. develop a hypothesis model to explain 2 5 - -
the discovered inferences
PC12. evaluate the results of the analysis and 3 5 - -
define business outcomes
PC13. define prescriptive actions based on the 3 5 - -
defined business outcomes
NOS Total 30 70 - -
IT-ITeS Sector Skill Council 15
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N8103
NOS Name Perform exploratory data analysis as per specifications
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 6
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 16
Qualification Pack
SSC/N8105: Apply pre-designed algorithmic models to specified use cases
Description
This unit is about applying a variety of pre-designed algorithmic models to specified use cases for internal
and external clients.
Scope
This unit/task covers the following:
Define hypothesis
Apply and optimize model
Elements and Performance Criteria
Define hypothesis To be competent, the user/individual on the job must be able to:
PC1. identify the objective of the analysis PC2. evaluate the dataset to determine a suitable approach PC3. identify suitable libraries, packages, frameworks, applications to address the objective Apply and Optimize Model To be competent, the user/individual on the job must be able to:
PC4. select suitable algorithmic models from available statistical analysis softwares, packages,
libraries or tools PC5. apply the model for various use cases and scenarios such as vision, text recognition, image
recognition, natural language processing etc. PC6. optimize selected algorithmic models to resolve any shortcomings or defects PC7. iterate the model in consultation with relevant stakeholders till the desired performance or
quality of output is achieved PC8. validate the models implemented using appropriate tools and processes PC9. create documentation on applied algorithmic models for future references and versioning
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the purpose and aims of the statistical analysis being undertaken
KU2. organizational policies, procedures and guidelines which relate to applying and
documenting algorithmic models KU3. different data sources and how to access documents and information from data sources
KU4. organizational policies and procedures for sharing data KU5. whom to consult when applying algorithmic models
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KU6. the range of standard templates and tools available and how to use Them
KU7. statistical analysis software, packages, libraries or tools with pre-designed algorithmic
models such as Mahout, BigML, Data Robot, Knime, Tensorflow KU8. programming languages that can be used to design algorithmic models such as python,
ruby, C, java, c++, c# etc. KU9. different use cases and the suitability of various algorithmic models to address them
KU10. how to build and test a hypothesis KU11. cloud or distributed computing platforms such as AWS, Azure, Hadoop, their affiliated
services and how to use these KU12. how to identify and refer anomalies in data KU13. various operating systems such as linux, ubuntu, or Windows
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. evaluate impact analysis of the various actions performed and disseminate relevant
information to others GS2. analyze data, models and understand its implications on business performance
GS3. check work completion without errors
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Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define hypothesis 8 17 - -
PC1. identify the objective of the analysis 2 3 - -
PC2. evaluate the dataset to determine a 3 7 - -
suitable approach
PC3. identify suitable libraries, packages,
3 7 - - frameworks, applications to address the
objective
Apply and Optimize Model 22 53 - -
PC4. select suitable algorithmic models from
5 15 - - available statistical analysis softwares,
packages, libraries or tools
PC5. apply the model for various use cases and scenarios such as vision, text recognition,
10 15 - - image recognition, natural language processing
etc.
PC6. optimize selected algorithmic models to 5 10 - -
resolve any shortcomings or defects
PC7. iterate the model in consultation with
2 3 - - relevant stakeholders till the desired
performance or quality of output is achieved
PC8. validate the models implemented using - 5 - -
appropriate tools and processes
PC9. create documentation on applied
- 5 - - algorithmic models for future references and
versioning
NOS Total 30 70 - -
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Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N8105
NOS Name Apply pre-designed algorithmic models to specified use cases
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 7
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 20
Qualification Pack
SSC/N8104: Perform research and design of algorithmic models
Description
This unit is about performing research and designing a variety of algorithmic models for internal and
external clients.
Scope
The scope covers the following:
Define hypothesis Select model Prototype and design
Elements and Performance Criteria
Define hypothesis To be competent, the user/individual on the job must be able to:
PC1. identify the objective of the analysis PC2. develop a hypothesis based on the objective of the analysis PC3. identify suitable libraries, packages, frameworks, applications to address the objective Select model To be competent, the user/individual on the job must be able to:
PC4. identify mode of learning, i.e. supervised or unsupervised PC5. conduct research on existing statistical models to evaluate fitment with the objective PC6. depending on the use case, identify if neural networks or deep learning models can be built PC7. optimize the existing statistical models as per need PC8. identify suitable statistical models on the basis of data volumes and key variables
PC9. define connectors or combinations of key variables for each statistical model Prototype and Design To be competent, the user/individual on the job must be able to:
PC10. determine and collect the training data PC11. design and prototype algorithmic model
PC12. identify and resolve overfitting or underfitting of algorithmic model
PC13. identify and resolve residual and dispersion errors with data PC14. define data flows such as human-in-the-loop constraints required to reinforce algorithmic
models PC15. define and quantify success metrics for the algorithmic model PC16. create documentation on designed algorithmic models for future references and versioning PC17. retrain datasets that have been used for supervised learning on a continuous basis PC18. validate designed models using appropriate tools and processes
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PC19. Iterate the process to fine-tune the model till the desired quality of output or performance is
achieved
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the purpose and aims of the analysis being undertaken
KU2. organizational policies, procedures and guidelines which relate to designing and
documenting algorithmic models KU3. different data sources and how to access documents and information from data sources
KU4. organizational policies and procedures for sharing data KU5. whom to involve when designing algorithmic models KU6. the range of standard templates and tools available and how to use them KU7. ability to develop experimental and analytical plans for data modelling, use of strong
baselines, ability to accurately determine cause and effect relations KU8. probability theory concepts such as probability distributions, statistical significance, hypothesis
testing and regression KU9. Bayesian thinking concepts such as conditional probability, priors and posteriors, and
maximum likelihood KU11. strong research experience in deep learning, reinforcement learning and other machine
learning algorithms and their usage KU12. programming languages that can be used to design algorithmic models such as python,
ruby, C, java, c++ or c# KU13. use cases and the suitability of various algorithmic models to address them
KU14. how to build and test a hypothesis KU15. supervised or unsupervised learning KU16. Evaluation of data volumes and key variables KU17. how to define combinations of key variables KU18. optimization of overfitting or underfitting of algorithmic models and residual and dispersion
errors KU19. how to define data flows such as human-in-the-loop constraints required to reinforce
algorithmic models KU20. cloud or distributed computing platforms such as AWS, Azure, Hadoop, their affiliated
services and how to use these KU21. Identification of anomalies in data KU22. various operating systems such as linux, ubuntu, or Windows
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. evaluate impact analysis of the various actions performed and disseminate relevant
information to others
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Qualification Pack
GS2. analyze data, models and understand its implications on business performance
GS3. check work completion without errors
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Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define hypothesis 2 7 - -
PC1. identify the objective of the analysis - 2 - -
PC2. develop a hypothesis based on the 1 2 - -
objective of the analysis
PC3. identify suitable libraries, packages,
1 3 - - frameworks, applications to address the
objective
Select model 12 24 - -
PC4. identify mode of learning, i.e. supervised or 2 4 - -
unsupervised
PC5. conduct research on existing statistical 2 4 - -
models to evaluate fitment with the objective
PC6. depending on the use case, identify if
2 4 - - neural networks or deep learning models can be
built
PC7. optimize the existing statistical models as 2 4 - -
per need
PC8. identify suitable statistical models on the 2 4 - -
basis of data volumes and key variables
PC9. define connectors or combinations of key 2 4 - -
variables for each statistical model
Prototype and Design 14 41 - -
PC10. determine and collect the training data 2 4 - -
PC11. design and prototype algorithmic model 3 6 - -
PC12. identify and resolve overfitting or 2 4 - -
underfitting of algorithmic model
PC13. identify and resolve residual and 2 4 - -
dispersion errors with data
PC14. define data flows such as human-in-the-
1 3 - - loop constraints required to reinforce algorithmic
models
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Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
PC15. define and quantify success metrics for 2 4 - -
the algorithmic model
PC16. create documentation on designed
- 4 - - algorithmic models for future references and
versioning
PC17. retrain datasets that have been used for 2 4 - -
supervised learning on a continuous basis
PC18. validate designed models using - 4 - -
appropriate tools and processes
PC19. Iterate the process to fine-tune the model
- 4 - - till the desired quality of output or performance
is achieved
NOS Total 28 72 - -
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Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N8104
NOS Name Perform research and design of algorithmic models
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation Artificial Intelligence and Big Data Analytics
NSQF Level 7
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 26
Qualification Pack
SSC/N9001: Manage your work to meet requirements
Description
This unit is about planning and organizing your work in order to complete it to the required standards on
time.
Scope
This unit/task covers the following:
• Utilize resources
• Ensure compliance
Elements and Performance Criteria
To be competent, the user/individual on the job must be able to: Utilize resources
PC1. establish and agree work requirements with appropriate people PC2. keep immediate work area clean and tidy PC3. utilize time effectively PC4. use resources correctly and efficiently PC5. treat confidential information correctly Ensure compliance PC6. work in line with organizations policies and procedures PC7. work within the limits of job role PC8. obtain guidance from appropriate people, where necessary
PC9. ensure work meets the agreed requirements
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. priorities for the area of work
KU2. role, responsibilities, limits of the responsibilities and whom these must be agreed with, as
well as when to involve others
KU3. the importance of having a tidy work area and how to do this
KU4. how to prioritize the workload according to urgency and importance and the benefits of this
KU5. the organizations policies and procedures, especially for dealing with confidential information,
and the importance of complying with these
KU6. the purpose of keeping others updated with the progress of work
KU7. the purpose and value of being flexible and adapting work plans to reflect change
KU8. the importance of completing work accurately and how to do this IT-ITeS Sector Skill Council 27
Qualification Pack
KU9. appropriate timescales for completing the work and the implications of not meeting these for
self and the organization KU10. The resources needed for the work and how to obtain and use these
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. read instructions, guidelines, procedures, rules and service level agreements GS2. ask for clarification and advice from line managers GS3. communicate orally with colleagues GS4. make decisions on suitable courses
GS5. plan and organize the work to achieve targets and deadlines
GS6. agree objectives and work requirements GS7. deliver consistent and reliable service to customers GS8. check that the work meets customer requirements GS9. refer anomalies to the line manager GS10. seek clarification on problems from others GS11. provide relevant information to others GS12. analyze needs, requirements and dependencies in order to meet the work requirements
GS13. apply judgment to different situations GS14. ensure the work is complete and free from errors GS15. get the work checked by peers GS16. work effectively in a team environment GS17. use information technology effectively, to input and/or extract data accurately GS18. identify and refer anomalies in data GS19. store and retrieve information GS20. keep up to date with changes, procedures and practices in the role IT-ITeS Sector Skill Council 28
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
25 75 - -
PC1. establish and agree your work - 6.25 - -
requirements with appropriate people
PC2. keep your immediate work area 6.25 6.25 - -
clean and tidy
PC3. utilize your time effectively 6.25 6.25 - -
PC4. use resources correctly and 6.25 12.5 - -
efficiently
PC5. treat confidential information - 6.25 - -
correctly
PC6. work in line with your organizations - 12.5 - -
policies and procedures
PC7. work within the limits of your job role - 6.25 - -
PC8. obtain guidance from appropriate - 6.25 - -
people, where necessary
PC9. ensure your work meets the agreed 6.25 12.5 - -
requirements
NOS Total 25 75 - -
IT-ITeS Sector Skill Council 29
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N9001
NOS Name Manage your work to meet requirements
Sector IT-ITeS
Sub-Sector IT Services
Primary Occupation Across all occupations
Secondary Occupation
NSQF Level 4
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 30
Qualification Pack
SSC/N9002: Work effectively with colleagues
Description
This unit is about working effectively with colleagues, either in your own work group or in other work
groups within your organization.
Scope
This unit/task covers the following:
• Communicate with colleagues • Show respect
Elements and Performance Criteria
To be competent, the user/individual on the job must be able to: Communicate with colleagues
PC1. communicate with colleagues clearly, concisely and accurately
PC2. work with colleagues to integrate the work effectively with theirs PC3. pass on essential information to colleagues in line with organizational requirements
Show respect
PC4. work in ways that show respect for colleagues PC5. carry out commitments one has made to colleagues PC6. identify any problems while working with colleagues and take the initiative to solve these
problems PC7. follow the organizations policies and procedures for working with colleagues
Knowledge and Understanding (KU) The individual on the job needs to know and understand:
KU1. the organizations policies and procedures for working with colleagues and the role and
responsibilities in relation to this KU2. the importance of effective communication and establishing good working relationships with
colleagues KU3. different methods of communication and the circumstances in which it is appropriate to use
these KU4. benefits of developing productive working relationships with colleagues KU5. the importance of creating an environment of trust and mutual respect in an environment
where there is no authority over those working with KU6. where do not meet the commitments, the implications this will have on individuals and the
organization KU7. different types of information that colleagues might need and the importance of providing this
information when it is required KU8. the importance of understanding problems from the colleagues perspective and how to
provide support, where necessary, to resolve these
IT-ITeS Sector Skill Council 31
Qualification Pack
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. complete accurate, well written work with attention to detail
GS2. communicate effectively with colleagues in writing GS3. read instructions, guidelines, procedures, rules and service level agreements
GS4. listen effectively and orally communicate information accurately GS5. ask for clarification and advice from line managers
GS6. make decisions on suitable courses of action GS7. plan and organize the work to achieve targets and deadlines GS8. ensure the work meets customer requirements, and deliver consistent and reliable service GS9. apply problem solving approaches in different situations GS10. apply balanced judgments to different situations GS11. ensure the work is complete and free from errors GS12. get the work checked by peers GS13. work effectively with colleagues and other teams in a team environment GS14. treat other cultures with respect GS15. identify and refer anomalies GS16. help reach agreements with colleagues GS17. keep up to date with changes, procedures and practices in the role
IT-ITeS Sector Skill Council 32
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
20 80 - -
PC1. communicate with colleagues clearly, - 20 - -
concisely and accurately
PC2. work with colleagues to integrate your - 10 - -
work effectively with theirs
PC3. pass on essential information to
20 - - - colleagues in line with organizational
requirements
PC4. work in ways that show respect for - 20 - -
colleagues
PC5. carry out commitments you have made - 10 - -
to colleagues
PC7. identify any problems you have working
- 10 - - with colleagues and take the initiative to solve
these problems
PC8. follow the organizations policies and - 10 - -
procedures for working with colleagues
NOS Total 20 80 - -
IT-ITeS Sector Skill Council 33
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N9002
NOS Name Work effectively with colleagues
Sector IT-ITeS
Sub-Sector IT Services
Primary Occupation Across all occupations
Secondary Occupation
NSQF Level 4
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 34
Qualification Pack
SSC/N9004: Provide data/information in standard formats
Description
This unit is about providing specified data/information related to your work in templates or other standard
formats.
Scope
This unit/task covers the following: • Obtain information
• Analyze and report information
Elements and Performance Criteria
To be competent, the user/individual on the job must be able to: Obtain information
PC1. establish and agree with appropriate people the data/information you need to provide, the
formats in which you need to provide it, and when you need to provide it PC2. obtain the data/information from reliable sources PC3. check that the data/information is accurate, complete and up-to-date PC4. obtain advice or guidance from appropriate people where there are problems with the
data/information
Analyze and report information PC5. carry out rule-based analysis of the data/information, if required
PC6. insert the data/information into the PC7. report any unresolved anomalies in the data/information to appropriate people PC8. provide complete, accurate and up-to-date data/information to the appropriate people in the
required formats on time
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. organizations procedures and guidelines for providing data/information in standard
formats and your role and responsibilities in relation to this
KU2. the knowledge management culture of your organization
KU3. organizations policies and procedures for recording and sharing information and the
importance of complying with these
KU4. the importance of validating data/information before use and how to do this
KU5. procedures for updating data in appropriate formats and with proper validation
KU6. the purpose of the CRM database
KU7. how to use the CRM database to record and extract information
KU8. the importance of having your data/information reviewed by others
KU9. the scope of any data/information requirements including the level of detail required
KU10. the importance of keeping within the scope of work and adhering to timescales
IT-ITeS Sector Skill Council 35
Qualification Pack
KU11. data/information one may need to provide including the sources and how to do this
KU12. templates and formats used for data/information including their purpose and how to use
these KU13. the techniques used to obtain data/information and how to apply these KU14. how to carry out rule-based analysis on the data/information KU15. typical anomalies that may occur in data/information KU16. whom to go to in the event of inaccurate data/information and how to report this
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. complete accurate, well written work with attention to detail
GS2. read instructions, guidelines, procedures, rules and service level agreements
GS3. listen effectively and orally communicate information accurately GS4. follow rule-based decision-making processes
GS5. make decisions on suitable courses of action GS6. plan and organize the work to achieve targets and deadlines GS7. check the work meets customer requirements and exceed customer expectations GS9. apply problem solving approaches in different situations GS10. configure data and disseminate relevant information to others GS11. apply balanced judgments to different situations
GS12. use information technology effectively, to input and/or extract data accurately
GS13. validate and update data
GS14. store and retrieve information IT-ITeS Sector Skill Council 36
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
25 75 - -
PC1. establish and agree with appropriate people the data/information you need to
12.5 - - - provide, the formats in which you need to
provide it, and when you need to provide it
PC2. obtain the data/information from reliable - 12.5 - -
sources
PC3. check that the data/information is 6.25 6.25 - -
accurate, complete and up-to-date
PC4. obtain advice or guidance from
- 12.5 - - appropriate people where there are problems
with the data/information
PC5. carry out rule-based analysis of the - 25 - -
data/information, if required
PC6. insert the data/information into the - 12.5 - -
PC7. report any unresolved anomalies in the 6.25 - - -
data/information to appropriate people
PC8. provide complete, accurate and up-to-date
- 6.25 - - data/information to the appropriate people in
the required formats on time
NOS Total 25 75 - -
IT-ITeS Sector Skill Council 37
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N9004
NOS Name Provide data/information in standard formats
Sector IT-ITeS
Sub-Sector IT Services
Primary Occupation Across all occupations
Secondary Occupation
NSQF Level 4
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 38
Qualification Pack
SSC/N9006: Build and Maintain relationships in a Workplace
Description
This unit is about building and maintaining constructive relationships at the workplace.
Scope
This unit/task covers the following: Build relationships Maintain relationships Appropriate people: line
manager, members of the team/department, members from other teams/departments
Build relationships
Maintain relationships
Elements and Performance Criteria
Build relationships To be competent, the user/individual on the job must be able to:
PC1. build rapport with appropriate people at the workplace
PC2. develop new professional relationships PC3. build alliances to establish mutually beneficial working arrangements
PC4. foster an environment where others feel respected PC5. identify and engage a diverse range of influential contacts Maintain relationships To be competent, the user/individual on the job must be able to:
PC6. obtain guidance from appropriate people, where necessary PC7. attentively listen to ideas and give constructive feedback PC8. promptly resolve conflicts between team members PC9. work with colleagues to deliver shared goals PC10. recognize the contributions made by colleagues
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. organizational policies and procedures for building relationships and their role and
responsibilities in relation to this KU2. different training programs to enable the development of relevant behavioural competencies
KU3. the importance of creating an environment of trust and mutual respect in the organisation KU4. the importance of effective communication in developing productive working relationships
with colleagues KU5. different types of information that colleagues might need and the importance of providing this
information when it is required
IT-ITeS Sector Skill Council 39
Qualification Pack
Generic Skills (GS) User/individual on the job needs to know how to:
GS1. ask for clarification and advice from line managers
GS2. work effectively in a team environment
IT-ITeS Sector Skill Council 40
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Build relationships 17 33 - -
PC1. build rapport with appropriate people at 3 7 - -
the workplace
PC2. develop new professional relationships 3 7 - -
PC3. build alliances to establish mutually 3 7 - -
beneficial working arrangements
PC4. foster an environment where others 4 6 - -
feel respected
PC5. identify and engage a diverse range of 4 6 - -
influential contacts
Maintain relationships 13 37 - -
PC6. obtain guidance from appropriate 3 7 - -
people, where necessary
PC7. attentively listen to ideas and give 3 7 - -
constructive feedback
PC8. promptly resolve conflicts between 2 8 - -
team members
PC9. work with colleagues to deliver shared 2 8 - -
goals
PC10. recognize the contributions made by 3 7 - -
your colleagues
NOS Total 30 70 - -
IT-ITeS Sector Skill Council 41
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N9006
NOS Name Build and Maintain relationships in a Workplace
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 6
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 42
Qualification Pack
SSC/N9007: Build and Maintain client satisfaction
Description
This unit is about building and maintaining satisfaction with clients
Scope
This unit/task covers the following: Define client requirements Ensure client satisfaction Clients: internal,
external
Define client requirements
Ensure client satisfaction
Elements and Performance Criteria
Define client requirement To be competent, the user/individual on the job must be able to:
PC1. gather the client context and requirements PC2. manage fluctuating client priorities and expectations Ensure client satisfaction To be competent, the user/individual on the job must be able to:
PC3. respond to requests in a timely and accurate manner PC4. continuously improve service based on client feedback PC5. plan deliverables based on client needs
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. organizational policies and procedures for working with clients and their role and
responsibilities in relation to this KU2. the importance of effective communication and establishing good working relationships with
colleagues KU3. methods of communication and the circumstances in which it is appropriate to use these KU4. types of information that clients might need and the importance of providing this information
when it is required IT-ITeS Sector Skill Council 43
Qualification Pack
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. communicate effectively with clients in writing
GS2. follow instructions, guidelines, procedures, rules and service level agreements
GS3. check that self/peers work meets customer requirements
GS4. deliver consistent and reliable service to customers
GS5. apply balanced judgments to different situations
IT-ITeS Sector Skill Council 44
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define client requirement 15 25 - -
PC1. gather the client context and 5 10 - -
requirements
PC2. manage fluctuating client priorities 10 15 - -
and expectations
Ensure client satisfaction 15 45 - -
PC3. respond to requests in a timely and 5 15 - -
accurate manner
PC4. continuously improve service based - 15 - -
on client feedback
PC5. plan deliverables based on client 10 15 - -
needs
NOS Total 30 70 - -
IT-ITeS Sector Skill Council 45
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N9007
NOS Name Build and Maintain client satisfaction
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 6
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 46
Qualification Pack
SSC/N9010: Convince others to take appropriate action in different
situations
Description
This unit is about convincing others to take appropriate action in different situations.
Scope
This unit/task covers the following: Define needs Persuade others Range: Appropriate people such as line
manager, members of the team/department, members from other teams / departments
Define needs
Persuade others
Elements and Performance Criteria
Define needs To be competent, the user/individual on the job must be able to:
PC1. gather needs of concerned people PC2. adapt arguments to consider diverse needs Persuade others To be competent, the user/individual on the job must be able to:
PC3. use small wins as milestones to gain support for ideas PC4. persuade with the help of concrete examples or evidences PC5. take defined steps to reach a consensus on the course of action
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. organizational policies and procedures for persuading people and their role and
responsibilities in relation to this KU2. types of information that people might need and the importance of providing this information
when it is required KU3. methods of communication and the circumstances in which it is appropriate to use these
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. ask for clarification and advice from appropriate people
GS2. listen effectively and orally communicate information accurately GS3. make decision on a suitable course of action GS4. apply balanced judgments to different situations
IT-ITeS Sector Skill Council 47
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define needs - 25 - -
PC1. gather needs of concerned people - 10 - -
PC2. adapt arguments to consider - 15 - -
diverse needs
Persuade others 30 45 - -
PC3. use small wins as milestones to gain 10 15 - -
support for ideas
PC4. persuade with the help of concrete 10 15 - -
examples or evidences
PC5. take defined steps to reach a 10 15 - -
consensus on the course of action
NOS Total 30 70 - -
IT-ITeS Sector Skill Council 48
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N9010
NOS Name Convince others to take appropriate action in different situations
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 6
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 49
Qualification Pack
SSC/N9014: Maintain an inclusive, environmentally sustainable
workplace.
Description
The unit is about implementing and improving diversity equality and inclusion in a sustainable and
environment friendly workplace.
Scope
This unit/tasks covers the following: Enrich policies to respect diversity; Reinforce practices/
regulations/policies to promote and improve equity (equality)/inclusivity; Emphasize sustainable
environmental practices.
Elements and Performance Criteria
To be competent, the user/individual on the job must be able to:
Element 1 – Sustainable Practices
PC1: optimize usage of electricity/energy, materials, and water in various tasks/activities/processes and
plan the implementation of energy efficient systems in a phased manner.
PC2: Segregate recyclable, non-recyclable and hazardous waste generated for disposal or efficient
waste management.
Element 2 – Respect diversity and strengthen practices to promote equity (equality)/inclusivity PC3: Understand the diversity policy of the organization and use internal & external communication to
colleagues to improve.
PC4: Comply with PwD inclusive policies for an adaptable and equitable work environment. PC5: Improve through specifically designed recruitment practices, PwD friendly infrastructure, job roles,
etc. PC6: Use and advocate for appropriate verbal/nonverbal communication, schemes and benefits of
PwD.
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the organization’s policies and procedures about gender inclusivity, equality and sustainability
while working with colleagues and your role and responsibilities in relation to this.
KU2. inclusive tools and practices of communication to acknowledge/validate, share and promote the cause of gender parity at workplace. For example - supporting women with mentorship programs. speaking out against discriminatory practices or harassment.
IT-ITeS Sector Skill Council 50
Qualification Pack
KU3. the concept of gender, gender equality and gender discrimination, and all forms of gender
discrimination, violence and inequality, including the current and historical causes of gender
inequality in the workplace.
KU4. how to maintain and provide a conducive work environment that is free from any harassment;
facilities and amenities to PwD to perform and excel in their role.
KU5. organization’s redressal mechanisms (like the POSH committee) to address harassment and
bias at the workplace, with awareness of prevalent legislations against bias and sexual
harassment.
KU6. initiatives towards efficient use of natural resources and energy, reduction and prevention of
pollution and promoting waste avoidance and recycling measures in line with internationally
disseminated technologies and practices.
KU7. knows all about various energy options including renewable and non-renewable with their
environmental impacts, health issues, usage, safety and energy security.
KU8. implications that any non-compliance with electricity and energy may have on individuals and the
organization.
KU9. know organization’s electricity first aid emergency procedures.
KU10. monitoring, measuring and reporting performance of environmental conservation.
KU11. different types of electricity accidents, safety and security and how and when to report these.
KU12. how to use the electricity/energy safety, accident reporting, emergency procedures and the
importance of these.
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. Read PwD instructions, guidelines, procedures, diversity policies/acts, rules and service level agreements.
GS2. Aware of one’s own gender identity and gender role; and respectful of the gender performances of others.
GS3. Organize team building or sensitization workshops to address gender biases, stereotypes and
potentially blind spots. GS4. Clarify personal norms and values related to energy production and usage as well as to reflect
and evaluate their own energy usage in terms of efficiency and sufficiency. GS5. Listen and communicate (oral) effectively and accurately on all PwD policies. GS6. Apply balanced judgments in gender diversity situations. GS7. Take action to reduce the carbon footprint of business activities and embed environmental
responsibility
GS8. Calibration session with employees to discuss gender biases, stereotypes and potentially blind
spots.
IT-ITeS Sector Skill Council 51
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
To be competent, the user/individual on the job must 20 80 - -
be able to:
PC1: Optimize usage of electricity/energy, materials, and water in various tasks/activities/processes and plan the implementation of energy efficient systems in a phased manner.
5 15 - -
PC2: Segregate recyclable, non-recyclable and hazardous waste generated for disposal or efficient waste management
5 15 - -
PC3: Understand the diversity policy of the organization and use internal & external communication to colleagues to improve
5 10 - -
PC4: Comply with PwD inclusive policies for an adaptable and equitable work environment.
0 10 - -
PC5: Improve through specifically designed recruitment practices, PwD friendly infrastructure, job roles, etc.
- 20 - -
PC6: Use and advocate for appropriate verbal/nonverbal communication, schemes and benefits of PwD.
5 10 - -
NOS Total 20 80 - -
IT-ITeS Sector Skill Council 52
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N9014
NOS Name Maintain an inclusive, environmentally sustainable workplace
Sector IT-ITeS
Sub-Sector IT Services, Business Process Management, Engineering R&D, Software
Product Development
Primary Occupation Generic
Secondary Occupation
NSQF Level 4
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 53
Qualification Pack
SSC/N8106: Evaluate risk of deploying algorithmic models
Description
This unit is about evaluating the risks in deploying algorithmic models and developing mitigation measures for
internal and external clients
Scope
This unit/task covers the following: Define model scope Analys ealgorithmic model Range: Risks such as
accidental or intentional biases, errors, frauds
Define model scope
Analyse algorithmic model
Elements and Performance Criteria
Define model scope To be competent, the user/individual on the job must be able to:
PC1. define the purpose and metrics for the algorithmic model PC2. define data sources used to design the model and data flows used to reinforce the model PC3. define and evaluate the assumptions used while designing the algorithmic model PC4. evaluate the range of expected outcomes of the algorithmic model Analyse algorithmic model To be competent, the user/individual on the job must be able to:
PC5. test the model with different inputs and identify the factors that are creating a deviation
from the expected outcomes PC6. estimate the risks involved in case the algorithmic model deviates from the expected
outcomes PC7. introduce checks and mitigation measures for each of the potential risks resulting from the
model PC8. create documentation on potential risks and the associated mitigation measures
PC9. validate risks and mitigation measures with appropriate stakeholders PC10. recommend and implement corrective actions to the model as required
PC11. evaluate the model for all possible use cases/scenarios
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the purpose and aims of the analysis being undertaken
KU2. organizational policies, procedures and guidelines which relate to evaluating risks associated
with algorithmic models and documenting model risks and mitigation measures KU3. data sources and how to access documents and information from data sources
KU4. organizational policies and procedures for sharing data
IT-ITeS Sector Skill Council 54
Qualification Pack
KU5. whom to involve when evaluating risk and recommending mitigations KU6. the range of standard templates and tools available and how to use them KU7. use cases and the suitability of various algorithmic models to address them KU8. factors that contribute to risks. For example: outdated, irrelevant or biased input data
insufficient sample sizes flawed design logic, coding errors etc. KU9. different mitigation measures along areas such as data selection, algorithm design, live use in
production etc. KU10. identification of anomalies in data KU11. various operating systems such as linux, ubuntu, or windows
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. follow rule-based decision-making processes
GS2. make a decision on a suitable course of action GS3. analyze data and activities GS4. evaluate impact analysis of the various actions performed and disseminate relevant
information to others GS5. check the work completion without errors
IT-ITeS Sector Skill Council 55
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define model scope 12 28 - -
PC1. define the purpose and metrics for the 3 7 - -
algorithmic model
PC2. define data sources used to design the
3 7 - - model and data flows used to reinforce the
model
PC3. define and evaluate the assumptions used 3 7 - -
while designing the algorithmic model
PC4. evaluate the range of expected outcomes 3 7 - -
of the algorithmic model
Analyse algorithmic model 18 42 - -
PC5. test the model with different inputs and
3 7 - - identify the factors that are creating a deviation
from the expected outcomes
PC6. estimate the risks involved in case the
8 12 - - algorithmic model deviates from the expected
outcomes
PC7. introduce checks and mitigation measures
5 10 - - for each of the potential risks resulting from the
model
PC8. create documentation on potential risks - 5 - -
and the associated mitigation measures
PC9. validate risks and mitigation measures - 2 - -
with appropriate stakeholders
PC10. recommend and implement corrective - 3 - -
actions to the model as required
PC11. evaluate the model for all possible use 2 3 - -
cases/scenarios
NOS Total 30 70 - -
IT-ITeS Sector Skill Council 56
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N8106
NOS Name Evaluate risk of deploying algorithmic models
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 7
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 57
Qualification Pack
SSC/N8107: Evaluate business performance of algorithmic models
Description
This unit is about evaluating the performance of deployed algorithmic models at meeting expected
business outcomes.
Scope
This unit/task covers the following: Define performance metrics Perform analysis on model performance Range: Optimization techniques such as mini-batch gradient descent,momentum, RMSprop, Adam,
Bayesian optimization, grid search, ridge regression
Define performance metrics
Perform analysis on model performance
Elements and Performance Criteria
Define performance metrics To be competent, the user/individual on the job must be able to:
PC1. identify the objective being addressed by the model PC2. define suitable evaluation criteria and metrics to evaluate model performance as per objective Perform analysis on model performance To be competent, the user/individual on the job must be able to:
PC3. evaluate the performance of the algorithmic model PC4. identify the hyperparameters to maximize model performance
PC5. test different hyperparameter configurations PC6. use best-fit hyperparameter configuration to maximize model performance
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the purpose and aims of the statistical analysis being undertaken
KU2. organizational policies, procedures and guidelines which relate to evaluating business
performance of algorithmic models
KU3. different data sources and how to access documents and information
KU4. organizational policies and procedures for sharing data
KU5. who to involve when evaluating performance of algorithmic models
KU6. the range of standard templates and tools and how to use them
KU7. performance metrics to monitor business outcomes of algorithmic models
KU8. methodological approaches for identifying model hyperparameters such as grid
search, random search, Bayesian optimization
KU9. how to tune hyperparameter configurations
KU10. Identification of anomalies in data
IT-ITeS Sector Skill Council 58
Qualification Pack
KU11. operating systems such as linux, ubuntu, or windows
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. evaluate impact analysis of the various actions performed and disseminate relevant
information to others GS2. check the work completion without errors
IT-ITeS Sector Skill Council 59
Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define performance metrics 6 14 - -
PC1. identify the objective being addressed 3 7 - -
by the model
PC2. define suitable evaluation criteria and
3 7 - - metrics to evaluate model performance as
per objective
Perform analysis on model performance 24 56 - -
PC3. evaluate the performance of the 6 14 - -
algorithmic model
PC4. identify the hyperparameters to 6 14 - -
maximize model performance
PC5. test different hyperparameter 6 14 - -
configurations
PC6. use best-fit hyperparameter
6 14 - - configuration to maximize model
performance
NOS Total 30 70 - -
IT-ITeS Sector Skill Council 60
Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N8107
NOS Name Evaluate business performance of algorithmic models
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 7
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
IT-ITeS Sector Skill Council 61
Qualification Pack
SSC/N8108: Define business outcomes and create visualizations from
results of the analysis
Description
This unit is about defining business outcomes from results of a statistical analysis and create visualizations to
report them.
Scope
This unit/task covers the following: Define the scope Report business outcomes Range: Graphical formats
such as pie charts, line graphs, scatter graphs, bar charts, column graphs, ring plots. Types of analysis such
as trend, moving average, regression, inferential, exploratory, predictive, confirmatory correlation,
association, forecasting, estimation, cluster, trend plotting
Elements and Performance Criteria
Define the scope To be competent, the user/individual on the job must be able to:
PC1. identify the objective of the analysis PC2. establish the purpose, scope, and target audience to report the business outcomes PC3. define the delivery mode and format (such as excel sheets, reports, APIs) to report the
business outcomes Report business outcomes To be competent, the user/individual on the job must be able to:
PC4. summarize the defined business outcomes into a narrative PC5. select suitable visualizations to represent the defined business outcomes PC6. present outcomes through visualizations using standard templates and agreed language
standards PC7. validate visualizations with appropriate people PC8. publish visualizations for consumption across all agreed formats
Knowledge and Understanding (KU)
The individual on the job needs to know and understand:
KU1. the purpose and aims of the statistical analysis being undertaken
KU2. organizational policies, procedures and guidelines which relate to creating visualizations KU3. different data sources and how to access documents and information from data sources KU4. organizational policies and procedures for sharing data
KU5. who to involve when defining business outcomes and creating visualizations
KU6. intended audiences for reporting business outcomes KU7. their organization's knowledge base and how to access and update this KU8. organizational processes and procedures for approving and publishing documents
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Qualification Pack
KU9. the range of standard templates and tools available and how to use these
KU10. statistical concepts such as distributions, hypothesis testing, confidence intervals etc. KU11. how to evaluate results of quantitative or qualitative analysis to define business outcomes
KU12. graphical formats for presenting data and how to create these KU13. styles used in visualizations, including your organizations house style, types & templates KU14. applications, libraries or packages to create visualizations using tools such as Tableau,
Qlikview, d3js etc KU15. change management procedures, including version control and approvals
KU16. identification of anomalies in data KU17. various operating systems such as linux, ubuntu, or windows
Generic Skills (GS)
User/individual on the job needs to know how to:
GS1. complete accurate well written work with attention to detail
GS2. follow instructions, guidelines, procedures, rules and service level agreements GS3. check that your own and/or your peers work meets customer requirements GS4. work effectively in a customer facing environment GS5. analyze data and activities GS6. evaluate business impact and disseminate relevant information to others
GS7. check the work completion without errors
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Qualification Pack
Assessment Criteria
Assessment Criteria for Outcomes Theory Practical Project Viva
Marks Marks Marks Marks
Define the scope 15 30 - -
PC1. identify the objective of the analysis 5 10 - -
PC2. establish the purpose, scope, and target 5 10 - -
audience to report the business outcomes
PC3. define the delivery mode and format
5 10 - - (such as excel sheets, reports, APIs) to report
the business outcomes
Report business outcomes 15 40 - -
PC4. summarize the defined business 2 8 - -
outcomes into a narrative
PC5. select suitable visualizations to 3 7 - -
represent the defined business outcomes
PC6. present outcomes through visualizations
10 15 - - using standard templates and agreed
language standards
PC7. validate visualizations with appropriate - 5 - -
people
PC8. publish visualizations for consumption - 5 - -
across all agreed formats
NOS Total 30 70 - -
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Qualification Pack
National Occupational Standards (NOS) Parameters
NOS Code SSC/N8108
NOS Name Define business outcomes and create visualizations from results of the
analysis
Sector IT-ITeS
Sub-Sector Future Skills
Primary Occupation Artificial Intelligence & Big Data Analytics
Secondary Occupation
NSQF Level 6
Credits TBD
Version 2.0
Last Reviewed Date 31/03/2020
Next Review Date 31/03/2025
NSQC Clearance Date NA
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Qualification Pack
Assessment Guidelines and Assessment Weightage
Assessment Guidelines
1. Criteria for assessment for each Qualification Pack will be created by the Sector Skill Council. Each
Performance Criteria (PC) will be assigned marks proportional to its importance in NOS. SSC will also
lay down proportion of marks for Theory and Skills Practical for each PC.
2. The assessment for the theory part will be based on knowledge bank of questions created by the
SSC.
3. Assessment will be conducted for all compulsory NOS, and where applicable, on the selected
elective/option NOS/set of NOS.
4. Individual assessment agencies will create unique question papers for theory part for each
candidate at each examination/training center (as per assessment criteria below).
5. Individual assessment agencies will create unique evaluations for skill practical for every student at
each examination/training center based on this criterion.
6. To pass a QP, a trainee should score an average of 70% across generic NOS’ and a minimum of
70% for each technical NOS
7. In case of unsuccessful completion, the trainee may seek reassessment on the Qualification Pack.
Recommended Pass % : 70
Assessment Weightage
Compulsory NOS
National Occupational Theory Practical Project Viva Total Weightage
Standards Marks Marks Marks Marks Marks
SSC/N8101.Import Data as 30 70 - - 100 9
per specifications
SSC/N8102.Preprocess data 30 70 - - 100 9
as per specifications
SSC/N8103.Perform
30 70 - - 100 9 exploratory data analysis as
per specifications
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Qualification Pack
National Occupational Theory Practical Project Viva Total Weightage
Standards Marks Marks Marks Marks Marks
SSC/N8105.Apply pre-
30 70 - - 100 8 designed algorithmic models
to specified use cases
SSC/N8104.Perform research
28 72 - - 154 8 and design of algorithmic
models
SSC/N9001.Manage your 25 75 - - 100 5
work to meet requirements
SSC/N9002.Work effectively 20 80 - - 100 5
with colleagues
SSC/N9004.Provide
25 75 - - 100 5 data/information in standard
formats
SSC/N9006.Build and
30 70 - - 100 5 Maintain relationships in a
Workplace
SSC/N9007.Build and 30 70 - - 100 5
Maintain client satisfaction
SSC/N9010.Convince others
30 70 - - 100 4 to take appropriate action in
different situations
SSC/N9014. Maintain an inclusive, environmentally sustainable workplace
20 80 - - 100 4
Total 328 872 - - 1200 76
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Qualification Pack
Elective: 1 Model Risk Assessment
National Occupational Theory Practical Project Viva Total Weightage
Standards Marks Marks Marks Marks Marks
SSC/N8106.Evaluate risk
30 70 - - 100 24 of deploying algorithmic
models
Total 30 70 - - 100 24
Elective: 2 Model Business Performance
National Occupational Theory Practical Project Viva Total Weightage
Standards Marks Marks Marks Marks Marks
SSC/N8107.Evaluate
30 70 - - 100 24 business performance of
algorithmic models
Total 30 70 - - 100 24
Elective: 3 Visualizations
National Occupational Theory Practical Project Viva Total Weightage
Standards Marks Marks Marks Marks Marks
SSC/N8108.Define business outcomes and
30 70 - - 100 24 create visualizations from
results of the analysis
Total 30 70 - - 100 24
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