Course curriculum

  • 1

    Getting Started with Python

    • Programming 101

    • Python as a Data Science Tool

    • Jupyter Notebooks

    • Intro to Python

    • Intro to Numpy

    • Intro to Pandas

    • Intro to Matplotlib

    • Module Recap
  • 2

    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

    • Module Recap
  • 3

    Neural Networks & Deep Learning

    • Intro to Neural Networks and Deep Learning

    • Backpropagation Example

    • Training A Network With TensorFlow & Keras

    • Evaluating Performance of DL Models

    • Data Preparation

    • Advanced concepts

    • Module Recap
  • 4

    Computer Vision

    • What is Computer Vision?

    • Intro to OpenCV & Image Operations

    • Data Preprocessing and Augmentation with Keras

    • Deep Learning in Computer Vision

    • Transfer learning & advanced model architectures

    • Module Recap
  • 5

    Natural Language Processing

    • What is NLP?

    • Data preparation

    • Feature extraction using Bag of words

    • Word Embedding

    • Deep Learning in NLP

    • Module Recap
  • 6

    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

    • Module Recap