data science bootcamp - nightcourses.com...data science bootcamp 3 this 18-week project lead...

DATA SCIENCE BOOTCAMPPart time (Evening)

09 - 05 - 2019 | 04 - 10 - 2019

DublinTalent Garden Dublin

DATA SCIENCE BOOTCAMP 2

INDEX

The Bootcamp 3

Skills Acquired 5

Lesson Structure 6

The Contents 8

The Faculty 13

More info 16


This 18-week project lead syllabus teaches you the skills you need

to deliver data science projects effectively. The first 12 weeks

cover core skills and concepts in data science whilst advancing to

topics like deep learning and natural language processing to enable

you to meet modern business needs. Every week, you’ll do two

evening sessions that blend lecture and labs to ensure you get

practical experience that will help you become a successful

data scientist.

The course covers the fundamentals needed to be successful in

data science - coding, maths, data analysis, and working practices.

Once the basics are covered participants will take a deep dive

into different techniques for arriving at conclusions and making

predictions required to tackle a variety of business challenges. This

lab component puts data science products into production and

gives participants the opportunity to apply techniques to industry

data including census data, satellite imagery, autonomous cars

safety data and sentiments from live social media feeds.

THE BOOTCAMP

Breaking intoData Science

What is it?


Data science is crucial to modern business and this course is

designed for individuals who want to break into the industry. While

the fundamentals of data science are covered, participants

benefit from practical industry-led workshops that cover the

most popular technologies and platforms (R, Power BI) for

data science and their application. Participants get the unique

opportunity to work on two real project components; Bring Your

Own Data (BYOD) from their own business challenge which they

are working on and the second pre-defined data challenge based

on external host organisations. This is a great opportunity for

individuals to actually deliver predictive models that enable real

business value.

The course is ideal for people looking to acquire data science

skills - typically IT Professionals, Business & Data Analysts,

Scientists, and Software Engineers seeking to learn more, upskill

and gain competitive advantage from their data.

THE BOOTCAMP

Why

participate?

Who is this

course for?


• Comfortable with a robust data science process and able

to implement the process in your own projects

• Able to analyse data using popular platforms (R, Power BI)

and produce quality reports and conclusions

• Well-versed in multiple models / algorithms that can be

applied to make predictions and able to identify and imple-

ment the right ones for different data science challenges

• Knowledgeable about techniques for working with and

making predictions based on non-tabular data

• Understand deep learning and natural language processing

topics and their application

• Apply learning to your own dataset and other pre-defined

dataset challenges

• Aware of further resources for continued self-learning

• Build a portfolio of data projects and your network.

SKILLS ACQUIRED

By the end of this courseyou will be:


LESSON STRUCTURE

6.15pm Industry facilitator intro, high level recap of previous session 6.30pm Lecture, demonstration and business cases

7.30pm Break

7.45pm Practical Activity

8.45pm AMA “Ask me anything” session with industry facilitator

9.15pm Close


The contents


DATA SCIENCE OVERVIEW

• An overview of data science

• Data science specialisms

• Common data science projects

• Ethics in data science

DATA SCIENCE TOOLS

• Programming languages

• Databases

• Reporting tools

• Hardware and the cloud

MATHS FUNDAMENTALS

• Algebra

• Probability

• Matrix maths

• Numeric distributions

PLANNING DATA SCIENCE PROJECTS

• The data science process

• Project management and frameworks

• Managing project assets

• Planning for deployment

W E E K 1

W E E K 2

W E E K 3

W E E K 4


EXPLORATORY DATA ANALYSIS

• Connecting to data sources

• Cleaning data

• Summarising data

• Visualising data

DRAWING CONCLUSIONS USING INFERENCE

• Analysing distributions

• Hypothesis testing

• Simulations

• A/B tests

PREDICTING CONTINUOUS VARIABLES

• Regression overview

• Linear regression

• Decision trees

• Feature engineering and sampling strategies

PREDICTING DISCRETE OUTCOMES

• Logistic regression

• Decision trees and variants


• Regularisation and hyper-parameter tuning

W E E K 5

W E E K 6

W E E K 7

W E E K 8


ANALYSING IMAGES AND VIDEO

• Neural networks

• Tensorflow and Keras


• Leveraging existing solutions

ANALYSING TEXT

• Term frequency

• Topic detection

• Sentiment analysis

• Document similarity

OPERATIONALISING A MODEL

• APIs

• Docker

• Feature engineering

• Best practices

MONITORING AND UPDATING A MODEL

• Logging

• KPIs and dashboards

• Model maintenance routines

• Best practices

W E E K 9

W E E K 1 0

W E E K 1 1

W E E K 1 2

W E E K 1 3 - 1 8 P R O J E C T


Ruth KearneyRuth is an experienced education designer and facilitator

who has delivered a broad range of digital and innovation

programmes to graduate and executive level. She is passio-

nate about action-based learning and what the impact of

enriched learning experiences has on the individual, team

and organisation. Prior to joining Talent Garden as School

Director, Ruth as worked for Trinity Innovation & Entrepre-

neurship Hub and Hothouse Incubator in DIT.

SCHOOL STAFF

Aaron DoranAaron Doran is passionate about helping people reach their

potential. Possessing a PgDip in Adult Learning Theory from

the National College of Ireland, he studied Business with

Psychology prior to entering the learning space. Aaron has

a background leading the L&D function with Dublin NGO,

Focus Ireland. Prior to that, he launched EMEA technical

training at the international technology company, Indeed.

com. Aaron also volunteers with education charities in the

Dublin area.

School Director

Learning Manager


We are educators who are committed to the

student learning experience and to taking an

‘action learning’ approach to teaching. We do

this through delivering interactive lectures and

practical workshops that are grounded in theory

but focused on real-world application.

MEET THE FACULTY

13

TEACHERS

Steph LockeSteph is one of only fifty-eight individuals in the world to be

recognised with Microsoft’s Artificial Intelligence Most Valued

Professional award.She is the founder of Locke Data, a UK-ba-

sed data science consultancy. Steph’s got more than a decade

in both technical and managerial roles around Business Intelli-

gence and Data Science for startups and mature organisations.

She shares this knowledge through her consultancy, her new

Nightingale product, and her technical community work.

Dr. Finn MacleodDr. Finn Macleod is a former mathematician with a PhD

in predictive complexity. He has built, sold and designed

dashboards for clients such as Thomson-Reuters, Formula

1 (via Meshh) and Heineken. Finn and Edward Kibardin (the

ex-chief data scientist of Badoo) partner on the project

DataRefiner, a hybrid tool that uses deep learning and TDA

(topological data analysis) to understand and segment complex

data sets. Finn has also been known to do improv theatre in his

spare time.

Mick Cooney Mick is a quantitative analyst working on data science type

projects in financial services, primarily in insurance. Previously

he developed volatility forecasting models in trading businesses

focusing on North American equity and equity index derivatives.

He advises and assists financial services companies on

managing and implementing data-driven processes within their

organisations. A regular attender of tech-focused Meetups in

Dublin, he gives regular workshops on various statistical and

programming techniques as part of the Dublin Data Science

meetup.


Use of laptop for practical work and a passion

for all things data is required.What you need to bring to the class

Every Thursday & Friday

evening from 9 May to the

4 October 2019

Talent Garden Innovation

School, DCU Alpha Campus,

Glasnevin, Dublin 11

5,525 €

6.15 - 9.15 pm

6,500 €

MORE INFO

Payment

info

D A T E S P L A C E

E A R L Y B I R D

T I M E

R E G U L A R

Early-bird discount of 15% available for early bookings


Check out other Masterclasses and Bootcamps on our website

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data science bootcamp - nightcourses.com...data science bootcamp 3 this 18-week project lead...

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