For coders, engineers, and tech professionals.
Duration: 3 months | Time: 60–70 hours
Advanced AI & ML concepts
- Transfer Learning: Reusing a pre-trained model on a new but related problem.
- Multi-task Learning: Training a model to solve multiple related tasks simultaneously.
- Active Learning: Allowing the model to select the most useful data points to label.
Coding hands-on with real datasets
- Practical experience with real-world data challenges
- Learn data cleaning, transformation, and visualization techniques
- Work on datasets from industries like healthcare, finance, e-commerce, and more
Project-based learning
- Focus on problem-solving: Encourages critical thinking and creative solutions to complex challenges.
- Collaboration and teamwork: Learners work in groups, sharing ideas and building communication skills.
- Student-centered learning: Learners have more choice and voice in their projects, increasing motivation.
AI ethics and governance
- Fairness and Non-Discrimination: Avoid bias and ensure AI does not reinforce harmful stereotypes or unfair treatment.
- Accountability: Clear responsibility for decisions made by AI; humans must remain in control.
- Ethical Frameworks & Guidelines: Adopt company or sector-wide ethics codes for AI development and use.
- Continuous Learning and Adaptation: Update governance practices as AI technologies and societal expectations evolve.