Generative AI & Machine Learning
This advanced course combines foundational machine learning with cutting-edge generative AI techniques like GPT, GANs, and Transformers. It is tailored for developers, data scientists, and AI enthusiasts looking to create intelligent systems and AI-powered applications.
Objectives
- Understand core ML concepts and models (supervised/unsupervised)
- Build and evaluate ML models using Python & scikit-learn
- Explore neural networks and deep learning with TensorFlow or PyTorch
- Implement and fine-tune Large Language Models (LLMs)
- Learn prompt engineering and use of OpenAI, HuggingFace
- Develop GenAI applications using APIs or fine-tuning models
Training Approach
This course adopts a practical, project-driven approach to mastering machine learning and generative AI concepts. Learners engage in hands-on coding using Python, Jupyter Notebooks, TensorFlow, PyTorch, and APIs from platforms like OpenAI and Hugging Face. Each module features guided labs, real-world datasets, and model-building exercises. The training emphasizes understanding theory through application—via experiments, model tuning, and deployment of AI solutions. With capstone projects, prompt engineering labs, and mentorship, participants gain experience developing and integrating intelligent AI systems in real-world use cases.
Course Highlights
- Python for ML & AI (NumPy, Pandas, Scikit-learn)
- Deep Learning with CNNs, RNNs, Transformers
- Generative AI using GPT, DALL·E, and custom LLMs
- Prompt Engineering, Chatbot development, and GenAI tools
- Integration with real-time applications and APIs
- Ethical AI and responsible model deployment
Career Opportunities
- AI Engineer / Researcher
- Machine Learning Engineer
- Data Scientist
- NLP Engineer
- Generative AI Specialist
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Do I need a math background?
A basic understanding of linear algebra, statistics,and calculus is helpful.
What programming languages are used?
Primarily Python and associated AI/ML libraries.
Will I get to build my own GPT-like model?
Yes, we cover both using existing APIs and building simplified versions.
Is this course for beginners?
Suitable for beginners with some programming experience.
Do we learn about model fine-tuning?
Yes, fine-tuning pretrained models is included.
Will we deploy AI models to production?
Yes, using tools like Flask, FastAPI, or Streamlit, and deploying to cloud platforms.