AI-FUNDA.KZ1 ISBN: 979-8-90059-162-9
Introduction to Artificial Intelligence
Master AI with this comprehensive Introduction to Artificial Intelligence training, featuring 150 quizzes and 137 essential flashcards.
What you will be able to do
- AI Problem Solving: Mastery of state-space representation, search strategies, and constraint satisfaction to build efficient, goal-oriented intelligent agents.
- Machine Learning Engineering: Proficiency in the full ML lifecycle, including data preparation, feature engineering, and deploying models using modern MLOps practices.
- Generative AI & NLP: Advanced capability in utilizing transformers, large language models, and prompt engineering to create scalable, intelligent text-based applications.
- Responsible AI Governance: Deep understanding of bias mitigation, transparency, and regulatory standards required to deploy secure and ethical AI systems.
Intermediate Self-paced · 1 year access
26 Hands-On LiveLabs
Practice real IT tasks in guided environments.
- Real environments
- Auto-graded
- No installation
01 / About
About This Course
02 / Lessons & labs
See exactly what you will learn and practice
Lessons
13 Interactive Lessons · 68 topics01 Preface +
02 Foundations of Artificial Intelligence 5 topics · 1 LiveLab +
- Understanding Artificial Intelligence (AI)
- History and Evolution of Artificial Intelligence
- Types and Approaches to Artificial Intelligence
- Computational Foundations of AI
- AI Applications, Careers, and Professional Skills
1 LiveLab in this lesson — see the labs panel →
03 Intelligent Agents and AI Problem Solving 5 topics · 1 LiveLab +
- Foundations of Intelligent Agents
- Designing Agents with the PEAS Framework
- AI Environment Characteristics
- Problem Formulation and State-Space Representation
- Agent Architectures and Behaviors
1 LiveLab in this lesson — see the labs panel →
04 Knowledge Representation, Reasoning, and Uncertainty 5 topics · 3 LiveLab +
- Representing Knowledge in AI Systems
- Logic-Based Reasoning
- Expert Systems and Rule-Based AI
- Reasoning Under Uncertainty
- Sequential and Approximate Reasoning
3 LiveLab in this lesson — see the labs panel →
05 Search, Optimization, Planning, and Decision Making 5 topics · 5 LiveLab +
- Foundations of AI Search
- Uninformed Search Strategies
- Informed and Local Search
- Optimization and Constraint Satisfaction
- Planning, Games, and Sequential Decisions
5 LiveLab in this lesson — see the labs panel →
06 Data and Machine Learning Foundations 6 topics · 2 LiveLab +
- Data, Mathematics, and Statistics for Machine Learning
- Machine Learning Concepts and Paradigms
- The Machine Learning Workflow
- Data Preparation and Feature Engineering
- Foundational Machine Learning Algorithms
- Model Evaluation and Improvement
2 LiveLab in this lesson — see the labs panel →
07 Neural Networks, Deep Learning, and Reinforcement Learning 5 topics · 5 LiveLab +
- Neural Network Fundamentals
- Training Deep Learning Models
- Deep Learning Architectures
- Transfer Learning and Generative Deep Learning
- Reinforcement Learning
5 LiveLab in this lesson — see the labs panel →
08 Computer Vision, Speech, Robotics, and Multimodal AI 5 topics · 2 LiveLab +
- Foundations of Machine Perception
- Computer Vision
- Speech and Audio AI
- Robotics and Autonomous Systems
- Multimodal and Edge AI
2 LiveLab in this lesson — see the labs panel →
09 Natural Language Processing and Generative AI 6 topics · 2 LiveLab +
- Natural Language Processing Foundations
- Transformers, Foundation Models, and Large Language Models
- Generative AI Models and Capabilities
- Prompt Engineering
- Retrieval-Augmented Generation and AI Agents
- Evaluating Generative AI Solutions
2 LiveLab in this lesson — see the labs panel →
10 Responsible, Ethical, Secure, and Governed AI 6 topics · 2 LiveLab +
- Responsible AI Principles and Social Impact
- Bias, Fairness, and Inclusion
- Transparency, Explainability, and Accountability
- AI Privacy, Security, and Safety
- AI Governance, Regulation, and Standards
- Responsible Use of Generative AI
2 LiveLab in this lesson — see the labs panel →
11 AI Engineering Lifecycle, Tools, and MLOps 6 topics · 1 LiveLab +
- Identifying and Defining AI Opportunities
- The AI Development Lifecycle
- AI Programming Tools and Platforms
- MLOps and AI Operations
- Monitoring, Testing, and Maintenance
- Project Management and Documentation
1 LiveLab in this lesson — see the labs panel →
12 AI Applications Across Industries and the Workforce 8 topics · 1 LiveLab +
- AI in Healthcare and Life Sciences
- AI in Business, Finance, and Retail
- AI in Manufacturing, Supply Chain, and Robotics
- AI in Transportation and Smart Mobility
- AI in Education and Research
- AI in Cybersecurity and Public Services
- AI in Media and Creative Industries
- AI in Workplace Productivity and Automation
1 LiveLab in this lesson — see the labs panel →
13 Future Horizons and Capstone Project 6 topics · 1 LiveLab +
- Emerging AI Trends
- Human-AI Collaboration and the Future of Work
- Academic, Career, and Portfolio Pathways
- Capstone Planning and Requirements
- Capstone Design and Prototype Development
- Capstone Evaluation, Presentation, and Reflection
1 LiveLab in this lesson — see the labs panel →
Hands-On Labs Our edge
26 LiveLabs- Understanding How AI Systems Work
- Designing an Intelligent Agent
- Calculating Probability Using a Bayesian Network
- Calculating Posterior Probability Using Bayes’ Theorem
- Calculating Probability of an Event
- Performing Iterative-Deepening Search (IDS)
- Performing Breadth-First Search (BFS)
- Performing Depth-First Search (DFS)
- Performing Uniform-Cost Search (UCS)
- Performing Greedy Best-First Search and A* Search
- Calculating Descriptive Statistics for a Dataset
- Calculating a Linear Regression Prediction
- Calculating the Artificial Neuron Output
- Calculating Batches per Epoch
- Calculating Mean Absolute Error (MAE)
- Calculating Mean Squared Error (MSE)
- Calculating the Updated Q-Value
- Testing ASR in Customer Support
- Analyzing an Image with Multimodal AI
- Create Multimodal Learning Content with AI
- Designing and Refining Effective Prompts
- Evaluating an AI System for Responsible AI and Risk
- Assessing Generative AI Content for Responsible Use
- Planning an AI Solution for a Cafe
- Understanding AI in Everyday Life
- AI Engineer Telephonic Interview
03 / FAQs
Questions before you start
Is this Introduction to Artificial Intelligence course suitable for absolute beginners?+
How does this course prepare me for certification?+
What is the primary trade-off in this curriculum?+
Build Your AI Skills
Develop practical skills in machine learning, generative AI, NLP, MLOps, and responsible AI through hands-on learning and practice.
- 1 year of full access
- 26 LiveLab included
- Certificate of completion
No credit card required