Data ScienceCERTIFIED

BOOTCAMP SYLLABUS

The Process

STEP 2 STEP 3 STEP 4 STEP 5 STEP 6STEP 1

Get paired with a 1-on-1 expert mentor

Complete exercises online

Your mentor reviews your work within hours

Perfect your skills over 3-6 months

Create a portfolio, hone your CV, interview prep

Begin your new career in data science

Hyperiondev.com Page 2

Overview

Going beyond the essentials

Hyperiondev.com Page 3

Outcomes of the bootcamp:

Mentors powered by CoGrammar

Hyperiondev.com Page 4

Our 1-on-1 code review centric approach works

Here’s why learning through code review is smarter

Be exposed to the industry standards from day one

Don’t make the same mistakes as computers

Industry experts tailored to your goals

Join a community of career-changers

Free of fear of failure

We layer a proven 1-on-1 personalised mentorship approach over our code review

Get unstuck with technical help

Hyperiondev.com Page 5

Why choose data science as a lucrative career?

How we get you hired

Technical CV and portfolio

Interview preparation Join our hiring network

Responsibilities include:

Career paths

The Data Analyst

Average salaries

Average salaries

Responsibilities include:

The Machine Learning Engineer

Hyperiondev.com Page 6

Responsibilities include:

The Data Scientist

Average salaries

Hyperiondev.com Page 7

Structure of the bootcamp

Free trial

Before you start

Python for Data Science

Beginner level

Data Analytics and Exploration

Intermediate level

Machine Learning and AI

Advanced level

Interview and getting hired

Post graduation

Hyperiondev.com Page 8

Tasks: Capstone Projects:

Breakdown of syllabus

12Remember, with HyperionDev, you’re never alone. You can contact your mentor for 1:1 support whenever you need help with a task. The code you submit for each task is reviewed by your mentor

Python for Data Science

Tasks

1

Description

Thinking logically: Pseudocodeand algorithm design

Introduction to Python

Numerical data types

The string data type

Control Structures: If else

The boolean data type and logical operators

Control Structures: While & For Loops

Working with external data sources: Input

Control Structures: Elif Statements

Capstone Project I: Nested loops

2

3

4

5

6

7

8

9

10

11

Hyperiondev.com Page 9

Discover the different types of errors that might occur in your programs and how to handle them.

Defensive programming: Error handling

12

Beginner data structures: Lists

Working with external data sources: Output

Functions: Using built-in functions

Introduction to ObjectOriented Programming

Capstone Project II:Consolidation

Introduction to Natural Language Processing (NLP)

13

14

15

16

17

18

Semantic Similarity (NLP)

Capstone Project III: Introductory NLP

19

20

Hyperiondev.com Page 10

Data visualisation I7

1

Introduction to databases

Design and build relational database

Sources of data

Working with SQL

SQLite

Capstone Project I: Databases

2

3

4

5

6

Tasks Description

Tasks: Capstone Projects:

Data Analytics & Exploration

Understand basic data visualization and how to choose the best form of visualisation based on aspects such as nature of dataset and expectations from the visualisation exercise.

21

Data Structures:Lists & Dictionaries

Get introduced to principles of object oriented programming to use them later with machine learning libraries.

Learn about sentiment similarity, a popular application of NLP widely used for social media analysis.

Use all the knowledge you have gained throughout this level to create a useful program.

Data visualisation II

Python packages for Data Science

8

9

10

Working with datasets11

12

Exploratory Data Analysis

Data analysis II

13

14

15

16

Hyperiondev.com Page 11

Capstone Project III: Data Visualization

17

18

Dive into more complicated data visualisation. Scatterplot matrix. Network visualization.

Data Visualization III Explore popular data visualization tools such as Tableau.

Get introduced to some of the most popular Python packages like pandas, NumPy, SciPy.

Understand how to deal with Missing Values and turn categorical variables into quantitative variables. Explore data normalisation.

Learn about descriptive statistics and concepts such as GroupBy, Correlation, Analysis of Variance ANOVA.

Build an analysis report based on a dataset.

Learn how to import and export data in Python. Start importing and manipulating datasets.

Set up Matplotlib and understand how to start loading data from a CSV and NumPy + Panda. Create basic visualisation using Matplotlib, such as pie charts and bar graphs.

Learn about cleaning data, dataframe manipulation, and summarising data.

Data Visualization IV

Data analysis I

Capstone Project II: Data Analysis

Create advanced visualization using Matplotlib, including scatter-plots, time-series plotting, area charts, and 3D plots.

16 Build an analysis report based on a dataset.Capstone Project II: Data Analysis

Introduction to versioncontrol and Git

19

21

Explore the Git version control system and the GitHub collaboration platform.

20 Git basics

Build your brand I

Dive into using Git and discover how to set up a repository, use common Git commands, commit a modified file, view your project's history and branch.

Use GitHub to start building a portfolio of work that you can share with others to showcase your skills.

Data visualisation V

Create or update your LinkedIn profile to connect with a network of professionals and let people know about your skills.

Tasks: Capstone Projects:

Supervised learning V: Decision Trees II

Build Your Brand III

Unsupervised Learning II: Clustering II

Capstone Project I:Image Processing

7

8

9

Unsupervised Learning II:

Unsupervised Learning III: PCA

Clustering I10

11

12

Capstone Project II:Unsupervised Machine Learning

13

Neural Networks I: Introduction14

Tasks

2

Description

Supervised learning I: Simple Linear Regression

Introduction to Machine Learning

Build your Brand II

Learn different techniques to train neural networks using backpropagation.

Test your knowledge of unsupervised machine learning in this challenging task.

Neural Networks II:Training Neural Networks

Supervised learning III: Logistic Regression

Supervised learning II: Multiple Linear Regression

Supervised learning IV: Decision Trees I

3

1

4

5

6

Machine Learning and AI

Hyperiondev.com Page 12

22

Learn what linear regression is and when to apply it.

Explore more concepts such as multiple linear regression, and Training vs. Test Set.

Introduces the notion of classification, and the application of logistic regression to binary classification.

Join the Hyperion Connect community to make yourself visible to Hyperion hiring partners.

Become familiar with the fundamental concepts and terminology used in neural networks. Understand backpropagation and learn how to validate your models.

15

Add to your knowledge of unsupervised learning by studying dimensionality reduction.

Understand how to work on clustering algorithms such as k-means, a commonly used unsupervised learning algorithm.

Explore more unsupervised learning algorithms such as hierarchical clustering.

Hyperiondev.com Page 13

19

16

17

18

Neural Networks III:CNNs, Yelp reviews Practical

Neural Networks IV:Recurrent Neural Networks: Sample Project

Reinforcement Learning:Practical example of AlphaGo

Get introduced to Convolutional Neural Networks with sample projects.

Delve into the applications of Recurrent Neural Networks with a simple project to follow and work on.

Describe the concept of reinforcement learning including Markov Decision Processes, Q-Learning.

Machine Learning in the IndustryLearn about industry-relevant applications of machine learning in finance and healthcare.

21

20Capstone Project III:Consolidated Machine Learning

Challenge your knowledge of machine learning gained throughout this bootcamp in this final capstone project.

22 Build your brand VMake your mark by ensuring that all components of your online presence related to your professional brand are finalised.

Build your brand IVGet some pointers for a successful technical interview and connect with your Hyperion Connect team to arrange a mock interview.