Artificial Intelligence (AI) Online Course

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Course Highlights

Artificial intelligence is a field of computer science that builds systems able to learn, reason, and act using data, algorithms, and computational models.
To ensure comprehensive learning in AI, we structured the curriculum into modules that progress from foundations to advanced topics with practical projects.

Student will be able to:
Understand the fundamentals of Artificial Intelligence, Machine Learning, and Deep Learning
Apply mathematical foundations such as probability, statistics, and linear algebra to AI solutions
Develop Python programs for data analysis, visualization, and model building

Gain a solid foundation in AI concepts and programming with Python
Learn the mathematics behind AI to strengthen your problem-solving skills
Get hands-on exposure to data preprocessing, visualization, and modeling
Master advanced AI techniques such as neural networks, CNNs, RNNs, and GANs
Work on real-time projects like traffic sign recognition, crop disease prediction, and Alzheimer’s detection
Earn a NASSCOM-recognized certification to enhance employability and career prospects
Stay industry-ready with practical knowledge and tools used in AI research and applications

Students and freshers who want to start a career in AI, ML, or Data Science
Working professionals seeking to upskill in AI for career advancement
Engineers, IT graduates, and software developers aiming to transition into AI/ML roles
Business owners and entrepreneurs looking to integrate AI into their operations
Data analysts and researchers interested in applying AI to solve complex problems
Professionals curious about the growing demand and opportunities in Artificial Intelligence

Artificial Intelligence is a discipline of computer science that enables machines to perceive, learn, and make decisions. This program blends Python programming, mathematical foundations, data handling, and modern machine-learning techniques to build practical, industry-ready solutions.
To make you learn AI comprehensively, we have segmented the course into 4 levels and set the topic structure accordingly.
Level 1 – Foundations: Introduction to AI/ML/DL, Python fundamentals & advanced concepts, and the math behind AI—linear algebra, probability, statistics, and calculus
Level 2 – Data & Classical ML: Data collection, cleaning and exploration; NumPy, Pandas, Matplotlib for analysis & visualization; supervised/unsupervised learning with scikit-learn (classification, regression, clustering)
Level 3 – Deep Learning & Vision: Neural networks in practice; CNNs for vision, RNNs for sequences, and generative models (GANs) with hands-on implementation
Level 4 – Reinforcement Learning & Projects: Search and optimization techniques, RL fundamentals and algorithms, and real-time projects such as traffic sign recognition, crop disease prediction, and Alzheimer’s detection
Seemingly complex, AI is a powerful toolkit to automate decisions, uncover insights from data, and create intelligent products across industries

In this AI course, you will gain hands-on experience with essential tools used in the industry:

Skills you will develop