On-Going Programs
On-Going Programs
Title: Introduction to AI
Objectives:Understand the basics of AI. Familiarize with simple AI concepts and applications.
Week 1: Basics of AI
Day 1: Introduction to AI and its importance.
Day 2: Examples of AI in daily life (smartphones, virtual assistants).
Day 3: Simple algorithms and how machines learn.
Day 4: Introduction to basic coding (using Scratch).
Day 5: Hands-on activity: Create a simple game using Scratch.
Week 2: Practical AI Applications
Day 6: AI in games and entertainment.
Day 7: Understanding chatbots.
Day 8: Hands-on activity: Build a basic chatbot using Scratch.
Day 9: AI and robotics basics.
Day 10: Project day: Presenting the chatbot and game created.
Objectives: Dive deeper into AI concepts. Gain hands-on experience with basic AI tools.
Week 1: Understanding AI
Day 1-2: Overview of AI and its real-world applications.
Day 3-4: Introduction to machine learning and neural networks.
Day 5: Practical: Create a decision tree using a simple dataset.
Week 2: Coding for AI
Day 6-7: Basic programming with Python.
Day 8-9: Introduction to AI libraries (TensorFlow, Keras).
Day 10: Practical: Create a basic image classifier.
Week 3: AI Projects
Day 11-12: AI in image and speech recognition.
Day 13-14: Practical: Build a simple voice assistant.
Day 15: Introduction to AI ethics and safety.
Week 4: AI in Action
Day 16-18: Exploring AI applications in different fields (healthcare, education).
Day 19-20: Group projects: Developing an AI solution for a real-world problem.
Day 21: Presentations and feedback.
Title: Junior AI Developers
Objectives:Develop a strong foundation in AI concepts and programming.Work on complex AI projects.
Month 1: Fundamentals of AI
Week 1: Introduction to AI, machine learning, and deep learning.
Week 2: Python programming basics.
Week 3: Data science fundamentals.
Week 4: Practical: Create a data analysis project.
Month 2: AI Tools and Techniques
Week 1: Deep dive into AI libraries (TensorFlow, PyTorch).
Week 2: Practical: Build a neural network model.
Week 3: AI in computer vision.
Week 4: Practical: Create an object detection system.
Month 3: AI Projects and Ethics
Week 1: Natural language processing basics.
Week 2: Practical: Build a text classifier.
Week 3: AI ethics, biases, and safety.
Week 4: Group project: Develop an AI application to address a community issue.
Title: AI Innovators Target
Objectives: Advanced understanding of AI concepts and tools. Develop innovative AI projects.
Month 1: Advanced AI Concepts
Week 1: Machine learning algorithms in depth.
Week 2: Practical: Implement various algorithms.
Week 3: Introduction to reinforcement learning.
Week 4: Practical: Build a reinforcement learning model.
Month 2: AI and Big Data
Week 1: Big data and AI.
Week 2: Data preprocessing and visualization.
Week 3: Practical: Work with a large dataset.
Week 4: AI in big data analytics.
Month 3: AI in Different Domains
Week 1: AI in healthcare.
Week 2: AI in finance.
Week 3: AI in autonomous systems.
Week 4: Practical: Develop a domain-specific AI application.
Month 4: AI Project Development
Week 1: Project planning and idea generation.
Week 2: Data collection and preprocessing for projects.
Week 3: Model selection and training.
Week 4: Practical: Model evaluation and improvement.
Month 5: AI Ethics and Future Trends
Week 1: Deep dive into AI ethics.
Week 2: Future trends in AI.
Week 3: Practical: Addressing ethical issues in AI projects.
Week 4: Final project development.
Month 6: Presentation and Review
Week 1: Project finalization.
Week 2: Project presentations.
Week 3: Feedback and improvements.
Week 4: Showcase and certification.
Objectives:Comprehensive understanding of AI and its applications.Prepare students for advanced studies or careers in AI.
Semester 1: Foundation and Core Concepts
Month 1: Introduction to AI, machine learning, and deep learning.
Month 2: Python programming and AI libraries.
Month 3: Data science and data visualization.
Month 4: Practical: Build various machine learning models.
Month 5: Deep learning and neural networks.
Month 6: Practical: Develop and deploy a deep learning project.
Semester 2: Specializations and Advanced Projects
Month 7: Natural language processing and speech recognition.
Month 8: Computer vision and image processing.
Month 9: Reinforcement learning and autonomous systems.
Month 10: Practical: Specialized AI projects.
Month 11: AI ethics, laws, and societal impact.
Month 12: Capstone project: Develop an innovative AI solution.