AI with Python

Learning to program with Python, one of the most widely used languages in Artificial Intelligence, is the core of this program. You'll also focus on neural networks—AI's main building blocks.

AI with python

An Introduction to Python

  • Introduction about Python
  • Application areas of python
  • Installing Python
  • Introduction to python IDE like spyder,jupyter notebook
  • Editing Python Files
  • Getting Help
  • Python Reserved Words
  • Naming Conventions

 Basic Python and Data types

  • Basic Syntax
  • String Values
  • String Operations
  • Numeric Data Types
  • The print Function 
  • Introduction to different data collection options in python: Lists, Tuples ,Sets, Dictionaries
  • Basic operations on these data types like create, Sort, update, copy

Python Program Flow Control

  • Conditional blocks using if, else and elif
  • Simple for loops in python
  • For loop using ranges, string, list and dictionaries
  • Use of while loops in python Loop manipulation using pass, continue, break and else
  • Programming using Python conditional and loops block


  • Defining Your Own Functions
  • Organise python code using function
  • Passing Functions to a Function
  • Mapping Functions in a Dictionary
  • Powerful Lambda function in python.

Modules and Packages in python

  • Modules: Standard Modules – sys,math,time
  • The dir Function
  • Organizing python projects into modules
  • Importing own module as well as external modules
  • Understanding Packages

 Basic libraries in python

  • Basic Numpy for all the numerical and mathematical operations.
  • Introduction to Scipy (Scientific Python)
  • Data visualization using python Matplotlib and seaborn, Plotting Data
  • Python Fundamentals for Data Pre-processing
  • Introduction to Pandas and Scikit Learn
    • Defining Panda
    • Pandas – Creating and Manipulating Data
    • How to Create Data Frames
    • Importance of Grouping and Sorting
    • Understanding Scikit-Learn

Artificial Intelligence with Deep Learning in python

Ø An Introduction to Artificial Intelligence
Ø History of Artificial Intelligence
Ø Future and Market Trends in Artificial Intelligence
Ø Neural Networks and Perceptron
Ø Understanding Feedforward Networks & many more.

Neural Networks
Tensorflow Networks and Keras
Ø Introducing TF
Ø Computation Graph
Ø Tensors
Ø Perceptron
Ø Activation Functions
Ø Cost Functions
Ø Gradient Descent Backpropagation

Introduction to Keras
Ø Regression in TF and NN using Keras
Ø Classification in TF and NN using Keras

Implement some algorithms using ANN Conventional Neural Networks
Ø Intro to CNN
Ø Convolution Operation
Ø Activation Layer
Ø Pooling
Ø Flattening
Ø Full Connection
Ø Softmax, Argmax & Cross-Entropy

Implement some algorithms using CNN
Practical project with deep learning using real Datasets



Instructor-led live online classes

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On-time scheduled virtual classes with limited trainer-student ratio.

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