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DATA SCIENCE BOOTCAMPPart time (Evening)
DublinTalent Garden Dublin
DATA SCIENCE BOOTCAMP 2
INDEX
The Bootcamp 3
Skills Acquired 5
Lesson Structure 6
Course Content 7
The Faculty 12
More info 14
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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?
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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. Coding is not a
prerequisite as relevant pre-learning materials will be supplied.
THE BOOTCAMP
Why
participate?
Who is this
course for?
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• 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
• Able to show off your portfolio of data science projects
to your next employer
SKILLS ACQUIRED
By the end of this courseyou will be:
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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
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Course Content
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BRILLIANT BASICS
Brilliant Basics are designed to bring you up to speed quickly on the foundations of Data
Science. It’s impossible to cover everything but we have selected the most valuable areas
with strong business applications. Straight away there is a deep dive into exploring and
interacting with real datasets. We believe in cutting right through the noise and getting to
where the real value is and here you learn about data architecture, context and start testing
with simple data exploration techniques. You navigate existing data science scripts and
understand the basic structures used.
Key subject areas are covered through interactive lectures and hands-on work-
shops on machine learning, defining models and building math foundations. Practical
techniques are demonstrated, from regression to autoencoders.
Brilliant Basics takes an in-depth look at the process of data science and how to build
project management frameworks. Core to any successful data project is how to gather
data requirements and of equal importance is understanding the legal and business con-
text within which it operates.
DATA EXPLORATION
Data Exploration is about getting to know your data. This means connecting to relevant
data sources, cleaning your data and exploring mechanisms for building your domain
knowledge. This also involves understanding how to troubleshoot loading data,
checking values and overall integrity of the data. Also explored is the key soft skills
required to manage stakeholders involved in the data process with established best practi-
ces. Mastering data exploration allows you to deliver real business value. By summarising
and visualising data - producing actionable insights - we can make better decisions, grow
our customer base and evaluate and mitigate against risk. To achieve this you need to learn
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about core technical topics in greater depth. This module teaches you to draw conclu-
sions using inference - analyse distributions, test hypothesis, as well as setting up
effective simulations and A/B tests.
This leads to building probability distributions, predicting continuous variables and discrete
outcomes, exploring regressions, decision trees, feature engineering (deep learning) and
sampling strategies. With the help of our experts and practical exercises, set up your pro-
blem, determine outcomes, try different models, and interpret your outputs.
DATA VISUALISATION & MODELLING
Today’s enterprises have an enormous amount of data - traditional, structured data, as well
as dark data that enterprises are now lighting up with breakthroughs in natural language
processing, data extraction, and classification technologies.
In this section, learn to visually represent your data compellingly, simplistically and
beautifully. Communicate your insights by exploring best practices in creating visualiza-
tions. Understand theoretical aspects of data visualization and the literature supporting
them. Build your knowledge of tools and libraries such as Charticulator, Data Illustrator and
Blender to efficiently generate and model impactful visuals.
Modelling is about conceptualising complex data objects into a data model. Learn from real
business cases to wow your clients with intuitive models. Monitor and update your mo-
dels, log results, KPIs and build interactive dashboards. Master model maintenance
routines and best practices.
This section also includes a guest workshop from the Irish Centre for High End Computing
(ICHEC) where participants explore neural-net based image classification - how an image
is “seen” by the computer as a numerical matrix. Exploring the idea of convolutions and
illustrating them visually.
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THE BUSINESS OF DATA AND THAT DATA OF BUSINESS - MA-KING IT WORK!
Modelling, math, exploration and key soft skills combine in The Business of Data.
Hone in on niche practical techniques, as well as exploring the business context of the data
science discipline.
This section focuses on empowering you to find the right tools find the tools and data you
need by determining good sources of open and proprietary data. Master APIs - connecting
to them, their limitations and applications. Understand the concept of explainability and
counterfactuals. Learn about the impact of GDPR using case studies and experiment with
the code and tools involved in webscraping.
Explore the career path of a Data Scientist with guest lectures from senior data
scientists from a variety of disciplines. Examine the oversights and underestimations
frequently encountered in the professional environment as well as mitigations and oppor-
tunities to boost your career.
ACTION PROJECT
Put new skills and knowledge into practice. Combine theoretical and action-based
learning approaches to solving real life business challenges. With the support of our faculty,
apply your skills and knowledge in two A-Projects; an individual project taken from your
own work/experience and a group pre-defined project from one of our corporate partners.
Our A-Project is core to the overall philosophy of Talent Garden.
It is designed to enhance your portfolio and enable you to further develop crucial
business and management skills while also providing actionable solutions and
recommendations for implementation.
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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
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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 work-
shops 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.
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Use of laptop for practical work and a passion
for all things data is required.What you need to bring to the class
Talent Garden Innovation
School, DCU Alpha Campus,
Glasnevin, Dublin 11
5,525 €
6.15 - 9.15 pm
6,500 €
MORE INFO
Payment
info
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
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