Upskilling Computing Graduates
Advanced
Special Training Program
The Upskilling BS Computing Graduates – Advanced program is designed to bridge the gap between academic knowledge and industry expectations. It is designed to transform technically strong graduates into industry-ready professionals by focusing on modern software engineering practices, AI-driven development, cloud-native applications, and advanced full-stack technologies. The program emphasizes real-world problem solving, scalable system design, and AI integration in software workflows. Through intensive hands-on training, learners gain exposure to cutting-edge tools and frameworks aligned with current global industry demands.
Duration
160+ hours
2 Months @ 20 hours per week
Session Days
Weekdays
Weekends
Course Delivery
Classroom
Live Remote
Target Audience
Fresh Graduates
Early Career Professionals
Level
Intermediate to Advanced
Cost
USD 99 per month
PKR 30,000 per month
* Installments options are available
Program Features
The IT industry is rapidly evolving toward AI-integrated development, cloud-native systems, automation, and scalable web architectures. While many graduates have strong theoretical knowledge, they often lack exposure to modern stacks such as Next.js, DevOps pipelines, and AI-assisted coding tools. This program bridges that gap by equipping learners with advanced technical competencies, industry tools, and applied experience, enabling them to compete in global remote and local tech markets effectively.
Why to Study This Program?
Skills Learners Will Gain
Program Learning Outcomes
By the end of the program, learners will be able to:
Target Job Roles
Curriculum
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Introduction to Programming and Python ▸ Decision Making and Loops ▸ Functions and Modular Programming ▸ Object-Oriented Programming ▸ Exception Handling best practices ▸ Functional programming basics | ▸ Refactor mini projects using OOP principles ▸ Debugging exercises | ▸ Python 3.x ▸ VS Code ▸ Jupyter Notebook |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Algorithm analysis ▸ Big-O notation ▸ Arrays and dynamic arrays ▸ Linked lists ▸ Stacks and queues ▸ Hash tables ▸ Binary trees and BST ▸ Graph representation ▸ BFS and DFS ▸ Searching algorithms ▸ Sorting algorithms ▸ Time complexity optimization | ▸ Build LRU cache ▸ Implement graph traversal system ▸ Solve coding problems (LeetCode-style) | ▸ Python ▸ VS Code ▸ Online judge platforms |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ HTML5 and CSS3 ▸ JavaScript ▸ Next.js Advanced Frontend ▸ Backend with Node.js + Express / FastAPI ▸ Modern UI Development ▸ AI Integration in Web Apps | ▸ AI-powered blog platform ▸ Job portal with AI recommendation system | ▸ Next.js ▸ Node.js / FastAPI ▸ Tailwind CSS ▸ OpenAI API ▸ Postman |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ ER diagrams recap ▸ Normalization (3NF, BCNF) ▸ SQL DDL & DML commands ▸ Indexing strategies ▸ Joins and subqueries ▸ Transactions and ACID properties ▸ Query optimization | ▸ Design e-commerce database ▸ Optimize slow queries ▸ Build reporting dashboards | ▸ MySQL / PostgreSQL ▸ pgAdmin / MySQL Workbench |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Agile & Scrum advanced usage ▸ Git branching strategies (GitFlow) ▸ Code review practices ▸ Software architecture basics | ▸ Team-based GitHub project ▸ Pull request workflow simulation | ▸ Git & GitHub ▸ Jira / Trello ▸ VS Code |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ CI/CD pipelines ▸ Docker containers ▸ Kubernetes basics (intro) ▸ Cloud deployment basics | ▸ Containerize full-stack app ▸ Deploy using GitHub Actions ▸ Host app on cloud platform | ▸ Docker ▸ GitHub Actions ▸ AWS / Vercel |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Introduction to AI-Driven SDLC ▸ Prompt Engineering & Large Language Models ▸ Transformer Architecture & Code LLMs ▸ Advanced Code Generation & Refactoring ▸ Fine-Tuning & Custom Code Models ▸ AI-Generated Testing & Mutation Testing ▸ AI-Based Static Analysis & Bug Detection ▸ AI-Powered DevOps Fundamentals ▸ Autonomous CI/CD & Self-Healing Systems ▸ Building Autonomous Software Agents ▸ Multi-Agent Collaboration Systems ▸ Secure AI-Generated Code ▸ Advanced Security & Compliance ▸ Responsible AI in Software Development | ▸ Practical Work: ▸ Build AI chatbot ▸ Build resume analyzer tool ▸ Create AI-powered coding assistant | ▸ OpenAI API ▸ LangChain ▸ Python ▸ FAISS / Pinecone ▸ Node.js |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Technical communication ▸ Resume & LinkedIn optimization ▸ Interview preparation (technical + HR) ▸ System design interviews basics ▸ Team collaboration skills ▸ Workplace ethics | ▸ Mock interviews ▸ CV building workshop ▸ Presentation sessions | ▸ LinkedIn ▸ Google Docs ▸ Zoom / Meet |
| Project Activities | Deliverables | Tools & Technologies |
|---|---|---|
| ▸ Learners will build an AI-powered Full Stack SaaS Application, combining: ▸ Next.js frontend ▸ Scalable backend API ▸ SQL database ▸ AI integration (LLM + RAG) ▸ Docker deployment ▸ CI/CD pipeline | ▸ Project proposal ▸ A working live project Suggested Projects: ▸ AI Resume Screening System ▸ Smart Learning Platform ▸ AI Job Recommendation System ▸ Intelligent E-Commerce Platform ▸ AI Coding Assistant Tool | Any relevant tools ▸ Python, SQL ▸ MongoDB, React ▸ Express.js, Node.js ▸ GitHub ▸ Google AI Studio, Claude ▸ PowerPoint |