AI Programming with Python Course

Learn the foundations of neural networks and artificial intelligence – Python, Pandas, PyTorch, NumPy, Matplotlib, Linear Algebra, and Calculus in this AI Programming with Python Course online. These are the key techniques that enable you to explore the world of artificial intelligence. Furthermore, with the expert training from our experienced mentors, you will learn to build your own AI applications.


AI Programming with Python Training Course Online – Overview

If you are already aware of the fact that the demand for AI is skyrocketing, so is the demand for employees with AI skills and if you are willing to get into this highly demanded domain, then this AI programming with Python Course will be the right path to start your learning journey. In this AI with Python Programming Course Online, you will learn the foundational concepts and tools such as PyTorch, NumPy, Python, Calculus, and Linear Algebra.

AI with Python Course Online – Key Features

  • Trusted content.
  • Re-learn for free anytime in a year.
  • Rigorous assignments and assessments.
  • Learn at your own pace.
  • Mandatory feedback sessions.
  • Mock-interviews.
  • Hands-on real-time experience.
  • Free mentorship.
  • Live chat for instant solutions.
  • Job ready employees post-training.
  • End-to-end training.
  • Download the certificate after the course.
AI with Python – Skills Covered: Python. NumPy. Pandas. Matplotlib. PyTorch. Calculus. Linear Algebra.

AI Programming with Python Course Online – Benefits

As Python supports interpretive run-time and has an intuitive syntax, it is especially used for prototyping algorithms for AI. Furthermore, candidates who are skilled in AI programming with python will be in high demand in the market due to the readability and code-friendly syntax of Python.

Annual Salary
Hiring Companies
Job Wise Benefits
Python AI Developer

Hiring Companies

Python AI Course Online – Training Options

Self-Paced Learning

£ 1200

  • 1-year access to the AI with Python course content.
  • 1 capstone project.
  • Multiple assessments.
  • Continuous feedback sessions.
  • Access to the class recordings.
  • Assistance and support.
  • Download certification.
  • Free mentorship.

Online Boot Camp

£ 1000

  • Everything in Self-paced learning +
  • On-spot doubt clarification.
  • Interactive training sessions.
  • Sessions on the capstone project.
  • Live, online classroom training.
  • Mock-interviews.

Corporate Training

Customized to your team’s needs

  • 1-year access to the AI with Python course content.
  • 1 capstone project.
  • Multiple assessments.
  • Continuous feedback sessions.
  • Class recordings.
  • Assistance and support.
  • Certification after the course.

AI Programming with Python Training Course Online – Curriculum


Any individual or working professional who wants to make a career in AI and Python can join this AI Programming with Python training course online.


To join this AI programming with python course online, you need to have formal pre-requisites such as basic programming knowledge in any language and foundational knowledge of algebra. This enables you to grasp concepts easily and experience a smooth learning journey.

Course Content

  • Learn why we program.
  • Prepare for the course ahead with a detailed topic overview.
  • Understand how programming in Python is unique.
  • Understand how data types and operators are the buildingblocks for programming in Python.
  • Use the following data types: integers, floats, booleans, strings, lists, tuples, sets, dictionaries.
  • Use the following operators: arithmetic, assignment, comparison, logical, membership, identity.
  • Implement decision-making in your code with conditionals.
  • Repeat code with for and while loops.
  • Exit a loop with break, and skip an iteration of a loop with continue.
  • Use helpful built-in functions like zip and enumerate.
  • Construct lists in a natural way with list comprehensions.
  • Write your own functions to encapsulate a series of commands.
  • Understand variable scope, i.e., which parts of a program variables can be referenced from.
  • Make functions easier to use with proper documentation.
  • Use lambda expressions, iterators, and generators.
  • Write and run scripts locally on your computer.
  • Work with raw input from users.
  • Read and write files, handle errors, and import local scripts.
  • Use modules from the Python standard library and from third-party libraries.
  • Use online resources to help solve problems.
  • Object Oriented programming provides a few benefits over procedural programming. Learn the basics by understanding how to use Classes.
  • Learn how to use Anaconda to manage packages and environments for use with Python.
  • Learn how to use Jupyter Notebooks to create documents combining code, text, images, and more.
  • Learn the value of NumPy and how to use it to manipulate data for AI problems.
  • Mini-Project: Use NumPy to mean normalize an ndarray and separate it into several smaller ndarrays.
  • Learn to use Pandas to load and process data for machine learning problems.
  • Mini-Project: Use Pandas to plot and get statistics from stock data.
  • Learn how to use Matplotlib to choose appropriate plots for one and two variables based on the types of data you have.
  • Learn the basics of the beautiful world of Linear Algebra and learn why it is such an important mathematical tool.
  • Learn about the basic building block of Linear Algebra.
  • Learn how to scale and add vectors and how to visualize them in 2 and 3 dimensions.
  • Learn what a linear transformation is and how is it directly related to matrices. Learn how to apply the math and visualize the concept.
  • Learn about the world of Neural Networks and see how it relates directly to Linear Algebra.
  • VECTORS LAB - Learn how to graph 2D and 3D vectors.
  • LINEAR COMBINATION LAB - Learn how to computationally determine a vector’s span and solve a simple system of equations.
  • LINEAR MAPPING LAB - Learn how to solve problems computationally using vectors and matrices.
  • Visualize the essence of calculus. Learn why it is such a powerful concept in mathematics
  • Learn about the derivative, one of the most important tools in calculus.
  • See how a derivative can measure the steepness of a function and why it is such an important indicator in the world of machine learning.
  • Learn how to find the derivative of a composition of two or more functions, a very important tool in training a neural network
  • Learn more about derivatives while focusing on exponential and implicit functions.
  • Learn about the formal definition of a derivative through understanding limits.
  • Learn about the inverse of a derivative: the integral.
  • Learn more about the world of neural networks and see how it relates directly to calculus through an explicit example.
  • Acquire a solid foundation in deep learning and neural networks. Implement gradient descent and backpropagation in Python.
  • Learn about techniques for how to improve training of a neural network, such as: early stopping, regularization and dropout.
  • Learn how to use PyTorch for building deep learning models.

Python AI Programming Course Online – FAQs

If you are making your plans to learn artificial intelligence, then learning Python will help you in a great way as it is the most widely used programming language in artificial intelligence. Furthermore, most of the tools of artificial intelligence are built using python and thus, it will be very beneficial to learn AI programming with python.

If you want to advance your career in the field of artificial intelligence, then making the base strong is very crucial. Furthermore, this AI programming with python course online will make you learn all the foundational concepts of AI, math skills, and neural networks which are the main building blocks for AI. So, if you are just starting out, then this is the right course to start with.

Yes, AI involves coding, and anybody who wants to learn AI, and understand and develop solutions using AI need to have programming skills. As AI-based algorithms are used to imitate a human closely, the use of mathematics and programming plays a key role in creating solutions.