Artificial Intelligence Program

Artificial Intelligence Programme (48 Hours)

The Artificial Intelligence Programme is a 48-hour comprehensive course that provides a solid foundation in AI by blending theoretical knowledge with practical experience. The programme introduces students to the core concepts, tools, and applications of AI while emphasizing ethical considerations in AI deployment. Learners will develop foundational skills in Python programming, data preprocessing, mathematics, machine learning, and neural networks. Through hands-on practice, students will build, implement, and evaluate AI models, culminating in a mini AI project using real-world data that reinforces applied learning and real-world problem-solving.

Course Modules

1. Module 1: Introduction to Artificial Intelligence (6 Hours)
   • Definition, scope, and objectives of AI
   • History and evolution of AI
   • Real-world applications across industries
   • Differences between AI, Machine Learning, and Deep Learning
   • Ethical considerations and responsible AI practices
   • Overview of AI systems and components
2. Module 2: Python Programming for Artificial Intelligence (8 Hours)
   • Python fundamentals: variables, data types, operators, and control structures
   • Functions and modular programming
   • Python modules and packages relevant to AI
   • Introduction to AI libraries: NumPy, Pandas, Matplotlib
   • Loading, inspecting, and manipulating datasets in Python
3. Module 3: Data Handling and Preprocessing (8 Hours)
   • Structured vs unstructured data
   • Data collection, cleaning, and standardization
   • Handling missing or inconsistent data
   • Normalization, transformation, and feature selection
   • Preparing datasets for AI and machine learning models
4. Module 4: Mathematics and Statistics for AI (8 Hours)
   • Linear algebra essentials: vectors, matrices, operations
   • Probability concepts and distributions
   • Descriptive statistics: mean, median, variance, standard deviation
   • Data visualization techniques for understanding datasets
   • Applying mathematical principles in AI algorithms
5. Module 5: Machine Learning Fundamentals (10 Hours)
   • Introduction to machine learning concepts
   • Supervised and unsupervised learning
   • Regression, classification, and clustering techniques
   • Training, validation, and testing datasets
   • Model evaluation metrics: accuracy, precision, recall, F1-score
   • Overview of dimensionality reduction
6. Module 6: Neural Networks and Mini AI Project (8 Hours)
   • Fundamentals of neural networks and perceptron models
   • Network architecture: neurons, layers, weights, and activation functions
   • Training basics: forward propagation, loss function, gradient descent
   • Mini AI project: dataset selection, preprocessing, model building, evaluation, and result interpretation

Learning Outcomes

By the end of this programme, learners will be able to:

• Understand key concepts, applications, and ethical considerations of Artificial Intelligence.
• Write Python programs and leverage AI libraries for data handling and model development.
• Preprocess and transform structured and unstructured data for AI tasks.
• Apply mathematical and statistical principles in AI and machine learning models.
• Build, evaluate, and interpret basic machine learning models (regression, classification, clustering).
• Understand neural network fundamentals and implement a mini AI project using real-world data.