1. AI Fundamentals & Machine Learning

Duration: 6 weeks

Audience: Beginners, students, career switchers

Modules:

Introduction to AI & ML concepts

Python for AI (NumPy, Pandas, Matplotlib)

Supervised vs. Unsupervised Learning

Regression, Classification, Clustering

Mini Project: Predicting housing prices

Outcome: Strong foundation in ML basics, ready for advanced courses.

Certification: AI Fundamentals Certificate

2. Deep Learning & Neural Networks

Duration: 8 weeks

Audience: Professionals, engineers, advanced learners

Modules:

Neural network architecture basics

Convolutional Neural Networks (CNNs) for image recognition

Recurrent Neural Networks (RNNs) for sequence data

Hands-on with TensorFlow & PyTorch

Mini Project: Image classification model

Outcome: Ability to design, train, and deploy deep learning models.

Certification: Deep Learning Specialist Certificate

3. Generative AI & Large Language Models

Duration: 6 weeks

Audience: Advanced learners, entrepreneurs, content creators

Modules:

Introduction to Generative AI

Prompt engineering techniques

Working with GPT models & APIs

Ethical AI & bias considerations

Mini Project: Build a chatbot with GPT

Outcome: Practical skills in generative AI applications.

Certification: Generative AI Practitioner Certificate

4. AI for Business & Marketing

Duration: 4 weeks

Audience: Entrepreneurs, marketers, managers

Modules:

AI in customer analytics & segmentation

Chatbots for customer service

AI-driven personalization in marketing campaigns

Case studies: Retail, hospitality, e-commerce

Outcome: Ability to apply AI tools to boost business growth.

Certification: AI Business Strategist Certificate

5. Data Science & AI Tools

Duration: 10 weeks

Audience: Analysts, engineers, professionals

Modules:

Data preprocessing & visualization

Scikit-learn for ML workflows

Advanced analytics with Pandas & NumPy

Real-world projects (finance, healthcare, retail datasets)

Outcome: End-to-end data science project execution skills.

Certification: Data Science Professional Certificate

6. AI in Cloud & Edge Computing

Duration: 5 weeks

Audience: IT professionals, cloud engineers

Modules:

Deploying AI models on AWS, Azure, GCP

Edge AI applications (IoT, mobile devices)

Scaling AI solutions in production

Mini Project: Deploy ML model on cloud

Outcome: Skills to deploy AI solutions in real-world environments.

Certification: Cloud AI Engineer Certificate

Add-ons for All Courses

• Hands-on Projects – Each course includes practical projects.
• Certification – Industry-recognized certificates.
• Placement Assistance – Internship/job support with partner firms.
• Weekend Workshops – Special sessions on trending topics like robotics, generative AI, and AI ethics.