Artificial Intelligence: Build Cognitive Systems to Solve Real-World Problems
Develop the skills to build intelligent systems that can simulate human cognitive functions. This course gives you practical experience in designing, evaluating, and deploying artificial intelligence models.
Artificial intelligence powers today's most innovative technologies—from autonomous vehicles to natural language processing. This course walks you through algorithms, knowledge representation, and implementation techniques that make machines smarter. Gain the confidence to work with complex problems and develop robust systems.
What You'll Learn
- ✓Understand core AI concepts like search algorithms and knowledge representation.
- ✓Implement popular AI techniques like heuristic search and logic programming.
- ✓Design intelligent agents and formulate environments for problem-solving.
- ✓Learn to optimize AI systems for efficiency, accuracy, and performance.
- ✓Deploy AI agents for practical use in businesses and applications.
- ✓Build end-to-end AI pipelines from problem definition to execution.
Course Curriculum
Understand how AI drives innovation across multiple industries.
- What is Artificial Intelligence? History & Applications
- Types of AI: Narrow, General, and Super Intelligence
- AI workflow: Perception → Reasoning → Action
- Setting up Python environment (Anaconda, Jupyter)
- Overview of key libraries: NumPy, NLTK, OpenAI Gym
Formulate problems and utilize search algorithms for optimal solutions.
- Uninformed search: BFS, DFS, Uniform Cost
- Informed search: A* Search, Heuristics
- Local search algorithms and optimization
- Adversarial search and Minimax algorithm
- Constraint Satisfaction Problems (CSP)
Master the foundational logic and reasoning frameworks used in AI.
- Propositional Logic and Theorem Proving
- First-Order Logic and Inference Rules
- Forward and Backward Chaining
- Handling uncertainty with Probabilistic Reasoning
- Hands-on: Building an expert system for diagnostics
Learn computational methods for interpreting and generating human language.
- Text processing: Tokenization, Stemming, Lemmatization
- Part-of-Speech Tagging and Named Entity Recognition
- Bag of Words and TF-IDF representations
- Word Embeddings: Word2Vec and GloVe overview
- Project: Sentiment analysis classifier system
Learn how to process, analyze, and understand digital images and videos.
- Image formation, filtering, and edge detection
- Feature extraction and object recognition
- Image segmentation and contouring techniques
- Face detection and motion tracking basics
- Pipeline building with OpenCV and Python
Discover how agents learn to make decisions by acting in an environment.
- Markov Decision Processes (MDP) framework
- Value iteration and Policy iteration
- Q-Learning and Exploration vs. Exploitation
- Introduction to robotics and kinematics
- Project: Navigating a maze using reinforcement learning
Get started with deep neural networks and modern AI architectures.
- Perceptron and Multilayer Neural Networks
- Activation functions: ReLU, Sigmoid, Softmax
- Backpropagation and weight optimization
- Introduction to PyTorch / TensorFlow
- Hands-on: Image classification with MNIST dataset
Apply your learning to industry-grade AI projects and learn to deploy systems.
- End-to-end AI project walkthrough
- Model serialization and state saving
- Building REST APIs with Flask for AI models
- Deploying on Heroku / Render / AWS
- Capstone: Build and deploy an intelligent chatbot application
Course Materials Provided
- ✓In-Depth Video Lessons: Comprehensive video content covering all major AI techniques.
- ✓Hands-On Projects: Use real-world scenarios to build artificial intelligence applications.
- ✓Access to Resources: Get downloadable code, scripts, and system blueprints.
- ✓Knowledge Checks: Test your understanding after each module.
- ✓Industry Expert Insights: Learn practical tips and trends from AI professionals.
Who This Course Is For
- ✓Beginners: Individuals with no prior experience who want to explore a new field and build foundational knowledge from scratch.
- ✓Students: College or school learners aiming to gain skills that enhance their academic profile and support their career goals.
- ✓Professionals: Working individuals such as engineers, analysts, developers, or managers looking to upskill or transition into AI roles.
- ✓Tech Enthusiasts: Passionate learners who enjoy exploring emerging technologies and want hands-on experience with artificial intelligence.
