Hands-on interactive lessons

Get exposed to practical lessons that involve you writing code alongside your instructor to help you engage in hands-on learning.

Cheat Sheets

After completing the course, you will get access to a summary cheat sheet that summarizes the entire course in a single-page PDF. This PDF will be useful for you to review the concepts after completing the course.

Syllabus

Week 1: Data Science & Machine Learning

- What is Artificial Intelligence?
- Data Science Lifecycle Dissected
- Machine Learning- Problem Understanding- Exploratory Data Analysis
- Data Cleaning & Preparation
- Model Training & Testing

Week 2: Deep Learning

- Intro to Deep Learning
- Backpropagation example
- Training a neural network with Tensorflow & Keras
- Evaluating the performance of Deep Learning models
- Data preparation
- Advanced concepts

Week 3: Computer Vision

- What is Computer Vision?
- Intro to OpenCV
- Data Preprocessing
- Deep Learning in Computer Vision
- Advanced Architectures

Week 4: Natural Language Processing

- What is Natural Language Processing?

- Data preparation

- Bag-of-words

- Word Embeddings

- Deep Learning in Natural Language Processing

Week 5: Time-series Analysis & Prediction

- What are Time-series?- Types of Time-series Problems
- Understanding Time-series Datasets & EDA

- Preparing Time-series Datasets

- Building Time-series Models

- Evaluating Time-series models