Beginner AI Foundation
Course
Duration - 4 Months
About Program
This beginner friendly AI foundation syllabus is designed to introduce absolute beginners to the essential concepts, skills, and tools needed for Artificial Intelligence, focusing on practical learning and foundational Knowledge over four months.
Course Structure Overview
Introduction to AI and Programming
- What is Artificial Intelligence? History and branches of AI
- Introduction to Python programming: variables, data types, input/output, simple programs
- Basic mathematics for AI:
- Linear algebra fundamentals (vectors, matrices)
- Basic probability and statistics concepts
- Setting up your programming environment (Python, Jupyter notebooks)
Data Handling and Manipulation
- Understanding data: types and formats
- Data structures in Python: lists, dictionaries, arrays
- Data manipulation using Python libraries:
- NumPy for numerical data
- pandas for data frames and data cleaning
- Basics of data preparation: handling missing data, filtering, sorting
Introduction to Machine Learning
- What is machine learning? Overview of supervised and unsupervised learning
- Simple algorithms:
- Linear regression
- Classification basics (e.g., decision trees)
- Model evaluation basics: accuracy, confusion matrix
- Hands-on mini projects applying basic ML algorithms using Python
AI Applications, Ethics, and Project
- Real-world AI applications: chatbots, image recognition, recommendation systems
- Introduction to ethical AI: fairness, transparency, privacy concerns
- Building a simple AI project (e.g., a chatbot or image classifier)
- Presentation and review of projects
- Future trends in AI and career pathways
Learning Methods
- Short, clear lectures and demonstrations
- Hands-on coding exercises and mini projects
- Weekly quizzes and assignments
- Group discussions on AI ethics and applications
- Final mini project presentation
Skills You Will Gain
- Basic Python programming tailored for AI
- Understanding of key mathematical concepts for AI
- Ability to manipulate and prepare data for AI tasks
- Awareness of machine learning fundamentals and simple algorithms
- Knowledge of AI applications and ethical considerations
- Confidence to pursue further AI learning or entry-level roles
References and Resources
- Python Fundamentals and Data Manipulation tutorials (NumPy, pandas)
- Introductory AI and Machine Learning courses (e.g., Coursera’s AI Foundations)
- Beginner-friendly AI projects and exercises
- Ethical AI guidelines and case studies
*This syllabus follows expert recommendations for beginners starting AI, emphasizing a strong foundation in programming, math, and data skills before moving into machine learning and ethical AI applications