Diploma in Artificial Intelligence
The Diploma in Artificial Intelligence (AI) is a comprehensive, practice‑oriented program designed to equip learners with the essential technical skills needed to thrive in today’s AI‑driven world.
The Diploma blends programming, data analytics, machine learning, deep learning, and NLP, delivering a balanced mix of theory and hands‑on practical training.
Learners graduate job‑ready with the ability to build intelligent systems, automate workflows, analyze data, and create AI‑powered applications like chatbots and recommendation engines.
Apply NowDiploma in Artificial Intelligence (AI)
The Diploma in Artificial Intelligence (AI) is a specialized one‑year, SBTE‑approved professional program designed to equip learners with the foundational knowledge and practical skills required to enter the rapidly expanding world of AI, data science, and intelligent automation. The program blends theory with extensive hands‑on practice, enabling students to master essential tools such as Python, R, Machine Learning frameworks, NLP libraries, Data Engineering systems, and modern AI APIs.
Built around real-world applications, this diploma gradually progresses from fundamental ICT, programming, and data handling skills to advanced AI techniques—such as neural networks, deep learning models, transformers, and intelligent system development. By the end of the year, learners are capable of building and deploying AI-powered solutions including chatbots, recommendation engines, predictive models, and automated data workflows.
This program is designed for beginners, students, and working professionals who want to start a career in technology or advance into AI-related roles with a strong, industry-relevant portfolio.
Program Objectives
The Diploma in AI is designed to achieve the following objectives:
- To build a solid foundation in ICT, programming, data management, and analytics
- To introduce students to essential concepts of Artificial Intelligence, Machine Learning, and Deep Learning
- To develop practical skills in Python and R programming for data and AI applications
- To provide experience with AI frameworks, libraries, and APIs used in industry
- To enable students to analyze, interpret, and process structured and unstructured data
- To prepare learners to design, build, evaluate, and deploy real-world AI solutions
- To promote innovation, problem‑solving, and computational thinking
- To build confidence in applying AI concepts across different fields, including business, healthcare, education, and automation
Learning Outcomes
Upon successful completion of this diploma, students will be able to:
Technical Skills
- Apply fundamental concepts of ICT, programming, and database systems
- Write clean, efficient code using Python and R
- Work with NumPy, Pandas, ggplot2, dplyr, and other analytical libraries
- Build and evaluate machine learning models such as regression, classification, clustering, and neural networks
- Develop deep learning models using TensorFlow or PyTorch
- Perform advanced data preprocessing, visualization, and feature engineering
- Use NLP tools (NLTK, spaCy, Transformers) for text analysis and model development
- Apply big data concepts and work with frameworks like Hadoop and Spark
AI Applications & Project Capability
Develop intelligent applications, including:
- Chatbots
- Recommendation engines
- Predictive models
- Automated data pipelines
- Integrate and deploy AI solutions using APIs, cloud platforms, and webhooks
- Implement model tuning, optimization, and evaluation techniques
- Understand ethical AI, model transparency, and responsible data handling
Professional Competence
- Demonstrate practical problem‑solving skills using AI and data-driven approaches
- Work collaboratively on AI projects and communicate technical concepts clearly
- Build a professional project portfolio suitable for entry‑level AI and data roles
- Prepare for careers in AI support, data analysis, automation, and software development
The Diploma in Artificial Intelligence is a 1‑year regular program, divided into two intensive semesters focusing on foundational skills and advanced AI applications. Each semester includes theory, hands‑on lab work, and project-based learning, ensuring students gain real-world, industry-relevant expertise.
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Applicants must have completed Matric or Intermediate (Science/Arts) from a recognized board; no prior programming background is required. Candidates should possess basic computer literacy and a strong interest in AI, data, or technology-related fields
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| Subjects | Details | Hours & Marks |
|---|---|---|
| Introduction to Information & Communication Technology (ICT) |
| Hours: 64 (Theory 64) Marks: 100 |
| Financial Data Analysis with MS Excel |
| Hours: 64 (Theory 14 • Practical 50) Marks: 100 |
| Python Programming |
| Hours: 64 (Theory 14 • Practical 50) Marks: 100 |
| Data Management |
| Hours: 64 (Theory 14 • Practical 50) Marks: 100 |
| Semester-End Project |
| Hours: 64 (Practical) Marks: 100 |
Semester-II (6 Months | 384 Hours | 600 Marks)
| Course | Subjects / Details | Hours & Marks |
|---|---|---|
| AI Primer (ML, DL, Neural Networks) |
| Hours: 64 (Theory 14 • Practical 50) Marks: 100 |
| Natural Language Processing (NLP) Toolkit |
| Hours: 64 (Theory 17 • Practical 47) Marks: 100 |
| R Programming |
| Hours: 64 (Theory 14 • Practical 50) Marks: 100 |
| Machine Learning |
| Hours: 64 (Theory 17 • Practical 47) Marks: 100 |
| Deep Learning & ML APIs |
| Hours: 64 (Theory 17 • Practical 47) Marks: 100 |
| Final Project – Chatbot & Recommendation Engine |
| Hours: 64 (Practical)Marks: 100 |
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