Diploma in Artificial Intelligence

(3-Month Program)

Program Overview:

This diploma program is designed for university students and early professionals aiming to develop strong technical skills in Artificial Intelligence (AI). Through a hands-on and project-based approach, participants will gain foundational and advanced knowledge in machine learning, deep learning, and AI applications using industry-standard tools and platforms.

Sessions: 2 per week, 3 hours each

Learning Outcomes:

Understand core concepts in AI, ML, and Deep Learning.
Develop and evaluate machine learning models.
Build and deploy neural networks for vision and language tasks.
Work with real-world datasets and build practical AI applications.
Collaborate on AI projects using GitHub and present outcomes.

Weekly Breakdown & Curriculum Outline:

Module 1: Foundations of AI

Week	Topics	Core Skills	Approach	Coding/Platforms
1	History and Evolution of AI Types of AI: Narrow, General, Superintelligence Key Concepts: Data, Algorithms, Intelligence	AI basics, ethical considerations	Lectures, discussions	Python, Jupyter Notebook, Google Colab
2	AI in Domains: Healthcare, Finance, Education Introduction to AI Ethics and Societal Impacts Environment Setup: Python, Jupyter, GitHub, Colab	Setup of development environment	Hands-on setup	Python, Jupyter, GitHub, Colab

Module 2: Core Machine Learning

Week	Topics	Core Skills	Approach	Coding/Platforms
3	Supervised Learning: Regression and Classification Implementing Linear and Logistic Regression	Supervised learning, model evaluation	Hands-on labs, mini-projects	Scikit-learn, Pandas, Matplotlib
4	Unsupervised Learning: Clustering and Dimensionality Reduction Techniques: K-Means, PCA	Unsupervised learning	Hands-on labs, quizzes	Scikit-learn, Pandas
5	Model Evaluation: Accuracy, Precision, Recall, F1 Score Overfitting and Cross-validation Techniques	Model evaluation, bias-variance tradeoff	Mini-projects, peer review	Scikit-learn, Matplotlib

Module 3: Deep Learning & Neural Networks

Week	Topics	Core Skills	Approach	Coding/Platforms
6	Basics of Neural Networks: Perceptron, Activation Functions Build a basic neural net using TensorFlow/Keras	Neural networks, deep learning fundamentals	Hands-on coding, model building	TensorFlow, Keras
7	Convolutional Neural Networks (CNNs) for Image Tasks Transfer Learning with Pre-trained Models	CNNs, transfer learning	Model testing, case studies	TensorFlow, Keras
8	Natural Language Processing (NLP) and ChatGPT Implement Text Classification and Summarization	NLP fundamentals, transformer models	Hands-on NLP tasks	Hugging Face Transformers

Module 4: AI Applications & Capstone Project

Week	Topics	Core Skills	Approach	Coding/Platforms
9	Explore AI Applications in Real-world Scenarios Team Formation and Dataset Selection	End-to-end AI development, teamwork	Guided projects, mentorship	Full-stack Python + ML tools, GitHub
10	Project Phase 1: Data Collection, Cleaning, Preprocessing	Data engineering, preprocessing	Team collaboration	Pandas, Scikit-learn
11	Project Phase 2: Model Building, Testing, and Optimization	Model optimization, deployment	Peer collaboration	TensorFlow, Scikit-learn
12	Final Project Presentation and Feedback Certification Ceremony	Presentation, project defense	Demo sessions, feedback	GitHub, Presentation tools

Tools and Platforms:

Programming Language: Python
IDEs & Notebooks: Jupyter, Google Colab
Libraries: Scikit-learn, TensorFlow, Keras, Pandas, Matplotlib
Collaboration: GitHub
AI APIs: ChatGPT, DALL·E

Assessment Methods:

Weekly coding exercises and quizzes
Mid-course evaluation project
Final capstone project presentation

Program Fees:

PKR 80,000
(Exclusive of Tax)

Application Deadline:

10th, July 2025

Starting From:

12th, July 2025

Sessions:

2 per week, 3 hours each

Venue

EMEC @IoBM, Karachi

Registration

Program Facilitator

Dr. WAZIR ALI

Ph.D (Artificial Intelligence)
Assistant Professor, Program Head (IoBM)

AHMED ZULQARNAIN QADRI

Corporate Trainer
Cutting age AI Solution Architect