Getting Started with Deep Learning

Learn everything from understanding the fundamentals of Deep Learning to solving real-world problems using Convolutional Neural Networks (CNNs)

26 Tutorials

2 Exercises

Intermediate Level

100% Online

Self-paced

Our Alumni Work At

About What You Will Learn?Course Content Success Stories

About this course

The Online Deep Learning Bootcamp was an initiative by DPhi to help aspiring Data Scientists and Data Scientists alike to learn and apply the concepts of Deep Learning in real-life. The bootcamp was concluded with numerous positive feedback from the participants. However, we also received several requests from people who missed the bootcamps to either host another one soon or give them access to the learning materials and resources.

So, in the spirit of sharing knowledge, building data culture and democratizing data science learning, we are sharing the entire contents of the Online Deep Learning Bootcamp including learning materials, slides, notebooks, live sessions, etc. for everyone.

During this bootcamp, experts from industry & academia delivered live sessions on the different aspects of Deep Learning. They shared their knowledge and expertise in discussing how to approach a Deep Learning Problem. They illustrate the same by solving some interesting Data Science problems in the live sessions.

Also, since it’s a community effort, the entire contents are absolutely free from start to finish. All we ask for in return is your

Contributors & Instructors

Dipanjan Sarkar

Google Developer Expert, ML

Joinal Ahmed

AI Consultant at Google

Sai Gayatri

Sr. ML Engineer, Prudential NY

Dikscha Sapra

Sr. Data Analyst, HCL

Gunnika Batra

CS, UC San Diego | Sr. Analyst, EY

What you will learn?

Each module of this Online Deep Learning Bootcamp targets a particular area which will help you build your skills in one area at a time.

A broad overview of the Bootcamp:

Module 1: Fundamentals of Deep Learning and Neural Networks
Module 2: Neural Networks for Regression Problems
Module 3: Neural Networks for Classification Problems
Module 4: Optimising a Neural Network
Module 5: Understanding Convolutional Neural Networks (CNNs) & Applied problem-solving on the real-world dataset

Course Content

1. Fundamentals of Deep Learning and Neural Networks

Introduction to Deep Learning

Live Session: Introduction to Neural Networks & its working

Setting Up TensorFlow

Optional - Basic Mathematics & Statistics Refresher

Optional - Learning Unit - Machine Learning 101 Refresher

Introduction to tf.Keras and Tensors

Quiz

2. Neural Networks for Regression Problems

Session: Introduction to Neural Networks for Regression

Session Notebook - Neural Networks for Regression & Hyperparameter Tuning

3. Neural Networks for Classification Problems

Working of Neural Network

Binary Classification & Neural Networks

Session: Introduction to Neural Networks for Classification

Notebook (Session) - Neural Networks for Classification

Practice Exercise: Bank Note

4. Optimising a Neural Network

Session: Dive Deep into Vanilla Neural Networks

Session Notebook - Dive Deep into Vanilla Neural Networks

Optimizing a Neural Network Part 1

Optimizing a Neural Network Part 2

Assignment 1: Object Recognition

Quiz

5. Convolutional Neural Networks

Computer Vision & OpenCV

Digital Image Processing

CNN, Transfer Learning & Data Augmentation

Session: Convolutional Neural Networks (CNN) Essentials

Session Notebook: CNN Essentials

Learning Unit - Some Other Popular Neural Networks

Assignment 2: Recognize an Animal in an Image

Face Mask Recognition

Earn Recognition

Take the next step towards your Data Science learning journey and make most of the community learning

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