Software Development
Advanced Data Science: From Clustering to Deep Learning
Course Overview:
This comprehensive course equips professionals with advanced techniques in data science and machine learning. Spanning topics from clustering and recommendation systems to deep learning and forecasting, the program combines theoretical foundations with hands-on projects using real world data.
Key Learning Outcomes:
- Apply clustering, dimension reduction, and association rule mining
- Build and evaluate recommendation systems and NLP models
- Implement supervised learning models including decision trees, ensembles, and regressions
- Develop CNN and RNN-based deep learning models
- Perform time-series forecasting and survival analysis
Course Modules Include:
- Clustering & Segmentation
- Dimension Reduction (PCA, SVD)
- Association Rules & Market Basket Analysis
- Recommendation Systems
- Network Analytics
- Text Mining & Natural Language Processing
- Naive Bayes, kNN, Decision Trees
- Ensemble Methods (Bagging, Boosting, Random Forest)
- Linear & Logistic Regression, Regularization Deep Learning with CNNs and RNNs
- Survival Analysis & Time-Series Forecasting
Software Requirements
Category | Software | Purpose |
|
Programming Tools | Python + Jupyter Notebook | Data analysis & coding |
|
Data Libraries | Pandas, NumPy | Data handling & numerical operations |
|
Visualization Tools | Matplotlib, Seaborn | Charts & graphs |
|
Coding Environments | Google Colab / VS Code | Writing and running code |
|
Data Handling | SQL (MySQL/PostgreSQL) | Database queries |
|
Productivity Tools | Excel / Google Sheets | Basic data analysis |
|
Collaboration Tools | Git + GitHub | Version control & teamwork |
|
Optional Tools | Tableau / Power BI | Dashboards & business insights |
|
Course Schedule – 2 week session
Day | Topic | Format | Key Activities |
1 | Introduction to Data Science | · Video + Quiz | Overview, applications, career paths |
2 | Python for Data Science – Basics | · Notebook + Exercises | Variables, data types, loops, functions |
3 | Data Handling with Pandas | · Hands-on Coding | Reading CSV, filtering, grouping, cleaning data |
4 | Data Visualization | · Notebook + Demo | Using Matplotlib, Seaborn, basic charting |
5 | Statistics & Probability Essentials | · Video + Quiz | Mean, median, standard deviation, distributions |
6 | Exploratory Data Analysis (EDA) | · Project Task | Analyze and summarize a sample dataset |
7 | Introduction to Machine Learning | · Interactive Lesson | Supervised vs unsupervised learning, basic models |
8 | Model Building with Scikit-learn | · Hands-on Coding | Train/test split, regression/classification example |
9 | Evaluation & Tuning | · Notebook + Quiz | Accuracy, confusion matrix, cross-validation |
10 | Capstone Mini Project & Presentation | · Live Session | Present a simple analysis/model with findings |
Course Schedule – 4 Months Session
Week | Module | Topics Covered | Activities |
1 | Introduction to Data Science | · Career paths, tools, data science workflow | Video + Quiz + Discussion |
2 | Python Basics | · Variables, data types, loops, functions | Jupyter exercises + practice tasks |
3 | Advanced Python | · List/dict comprehensions, error handling, file operations | Coding notebooks + mini assignments |
4 | Numpy for Numerical Computing | · Arrays, broadcasting, indexing, vectorized operations | Hands-on notebooks + quiz |
5 | Data Wrangling with Pandas | · DataFrames, merging, filtering, missing values, groupby | Real dataset analysis |
6 | Data Visualization | · Matplotlib, Seaborn, Plotly basics | Chart creation exercises |
7 | Exploratory Data Analysis (EDA) | · Summary stats, correlations, visual insights | Guided EDA project |
8 | Statistics for Data Science | · Mean, median, std dev, distributions, sampling, CLT | Videos + quizzes + simulations |
9 | Probability Basics | · Probability rules, Bayes’ theorem, distributions | Interactive problems + notebooks |
10 | SQL for Data Science | · SELECT, JOINs, GROUP BY, subqueries | SQL Lab + case studies |
11 | Introduction to Machine Learning | · Supervised vs unsupervised, ML lifecycle | Theory + model exploration (scikit-learn) |
12 | Regression Techniques | · Linear regression, evaluation metrics, assumptions | Practice datasets + regression mini-project |
13 | Classification Models | · Logistic regression, KNN, Decision Trees | Coding notebooks + comparison task |
14 | Model Evaluation & Tuning | · Confusion matrix, ROC-AUC, cross-validation, hyperparameter tuning | Practical ML model tuning |
15 | Capstone Project Development | · EDA + model building + visualization | Independent work + mentor feedback |
16 | Capstone Presentation + Review | · Project presentation + feedback + final assessment | Live session + peer review + certificate |
Assessment Type | Purpose | Frequency |
Quizzes | Test basic concepts and theory | After each module |
Coding Assignments | Practice Python, data analysis, ML models | Weekly or biweekly |
Mini Projects | Apply skills on real-world datasets | Monthly |
Capstone Project | Demonstrate full workflow and knowledge | End of course |
Peer Reviews | Encourage collaboration and feedback | During project weeks |
Presentations | Assess communication and insights | Final week |
Assessment Needs
Instructor Information
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Contact:
Office hours or discussion platform:
Data Analytics
Course Title: Data Analytics Foundations – From Data to Insights
- Course Description
This course provides a comprehensive introduction to the fundamentals of data analytics, covering the entire data lifecycle—from collection and cleaning to analysis, visualization, and basic machine learning. Designed for beginners, it blends theoretical understanding with hands-on practice using industry-standard tools like Excel, SQL, Python, and Tableau. By the end of the course, students will be equipped to conduct data-driven decision-making and create actionable insights from raw data.
- Learning Outcomes
By the end of this course, learners will be able to:
- Understand key concepts in data analytics and its role in business.
- Collect and clean data from various sources and formats.
- Conduct exploratory data analysis and derive statistical insights.
- Perform SQL-based data queries and aggregations.
- Visualize data effectively using Excel, Tableau, and Python libraries.
- Apply foundational statistical techniques and interpret results.
- Build basic predictive models using machine learning.
- Complete a capstone project demonstrating the full data analytics process.
Module | Title | · Key Topics | Major Assignments/Projects |
1 | Introduction to Data Analytics (2 hours) | · Definition, business value, · key concepts, · tool overview, · analytics lifecycle | Quiz on concepts and lifecycle |
2 | Data Collection & Cleaning (4 hours) | · Data sources (DBs, APIs, scraping), formats, · cleaning techniques, · hands-on cleaning practice | Exercise: Clean a messy dataset in Excel/Python |
3 | Exploratory Data Analysis (EDA) (4 hours) | · Data distribution, descriptive stats, · visualizations, trends/patterns | Mini project: EDA using Python and Tableau |
4 | SQL for Data Analysis (5 hours) | · SQL basics, joins, subqueries, aggregations, functions | Case Study: Analyze sales data with SQL |
5 | Data Visualization (5 hours) | · Visualization principles, Excel, · Tableau/Power BI, · Seaborn | Hands-on project: Build interactive dashboard |
6 | Statistical Analysis & Data Interpretation (4 hours) | · Probability, hypothesis testing, regression, · A/B testing, correlation | Analysis task in Python using real-world data |
7 | Intro to Machine Learning (3 hours) | · Supervised vs unsupervised learning, · regression/classification basics, · predictive modeling | Practice: Build a simple ML model in Python |
8 | Capstone Project (3 hours) | · End-to-end analytics · project: data collection, · cleaning, analysis, · presentation | Final capstone project + dashboard presentation |
Assessment Needs
Assessment Type | Purpose | Weight |
Quizzes | Check understanding of concepts | 15% |
Hands-on Assignments | Practice technical skills per module | 25% |
Mini Projects | Deeper application of learning | 20% |
Capstone Project | Full workflow demonstration | 30% |
Participation | Engagement in discussions & submissions | 10% |
- Required Materials
- Excel or Google Sheets
- Python (via Anaconda or Google Colab)
- SQL editor (e.g., MySQL Workbench, DB Fiddle)
- Tableau Public or Power BI
Course Schedule
Week | Modules Covered | Milestones/Deadlines |
1 | Module 1 + Module 2 | Quiz 1 + Cleaning assignment |
2 | Module 3 | EDA mini project due |
3 | Module 4 | SQL case study due |
4 | Module 5 | Visualization project due |
5 | Module 6 | Statistical analysis task due |
6 | Module 7 | ML model practice task |
7–8 | Module 8 (Capstone Project) | Final capstone project + dashboard submission |
- Instructor Information
Name:
Background:
Contact:
Office hours or discussion platform:
Machine Learning with Python: Beginner to Intermediate
Overview:
Master the fundamentals of machine learning using Python. This hands-on course guides you from core concepts to real-world applications through structured modules, practical projects, and industry-standard tools.
What You’ll Learn:
- Core ML concepts: Supervised & Unsupervised Learning
- Python libraries: NumPy, Pandas, Matplotlib, scikit-learn
- Data preprocessing, visualization, and feature engineering
- Regression, classification, and clustering techniques
- Intro to neural networks with TensorFlow/Keras
- Complete end-to-end ML projects using real datasets
Projects Included:
- Predict house prices (Regression)
- Student pass prediction (Classification)
- Customer segmentation (Clustering)
- Titanic survival analysis (Data preprocessing)
- Final Capstone Project (Choose your dataset
Assessment Needs
• Assessment Type | Purpose | Frequency |
Quizzes | Test ML concepts (types, models, terms) | After each module |
Coding Assignments | Practice implementing ML algorithms | Weekly or per topic |
Mini Project | Apply learned models to real datasets | Mid-course |
Capstone Project | End-to-end ML model (train, test, evaluate) | End of course |
Peer Review (Optional) | Encourage feedback and comparison | During projects |
Presentation | Explain model choices and insights | With final project |
Course Schedule
Week | Topic | Key Focus Areas | Deliverables |
1 | Introduction to Machine Learning | ML types (Supervised vs Unsupervised), real-world use cases | Quiz + basic classification code |
2 | Data Preparation & Model Building | Data preprocessing, feature selection, regression models | Assignment: Train a regression model |
3 | Model Evaluation & Improvement | Overfitting, cross-validation, accuracy metrics, confusion matrix | Mini project: Model evaluation task |
4 | Capstone Project & Presentation | Full ML pipeline: clean, train, test, present results | Capstone project + presentation |
Software required:
Python, Jupyter Notebook, scikit-learn, Seaborn, TensorFlow/Keras, Kaggle datasets
Ideal For:
Beginners in ML, data science enthusiasts, and students looking to build a portfolio of ML projects.
Build your ML skills from scratch. One model at a time. Enroll now
Instructor Information
Name:
Background:
Contact:
Office hours or discussion platform:
AI & Machine-Learning Professional Program
Overview
A 3-month (60-hour) hands-on course that takes you from Python essentials to deep-learning, NLP, and reinforcement-learning techniques. Guided labs, mini-projects, and a capstone ensure you can build, tune, and deploy real AI/ML solutions.
Learning Outcomes
By the end of this course, learners will be able to:
- Understand basic Machine Learning conceptsincluding supervised and unsupervised learning.
- Identify appropriate ML algorithmsfor classification and regression tasks.
- Preprocess and prepare datafor machine learning using standard techniques.
- Build, train, and test simple ML modelsusing Python and relevant libraries (e.g., scikit-learn).
- Evaluate model performanceusing metrics like accuracy, precision, recall, and confusion matrix.
- Apply the complete ML pipelinein a real-world mini project and present actionable insights
Course Structure
Module | Hours | Key Skills |
1 Intro to AI & ML | 4 | AI types, ML vs DL, real-world use-cases |
2 Python for ML | 10 | NumPy, Pandas, EDA, data cleaning & viz |
3 Supervised Learning | 12 | Regression, classification, model metrics |
4 Unsupervised Learning | 8 | Clustering, PCA/t-SNE, anomaly detection |
5 Neural Networks & DL | 10 | TensorFlow/PyTorch, back-prop, NN design |
6 CNNs | 6 | Image processing, transfer learning |
7 NLP | 6 | Text prep, embeddings, sentiment analysis |
8 Reinforcement Learning | 2 | Q-Learning, deep Q-networks |
9 Capstone & Case Studies | 4 | End-to-end project, optimisation, demo |
Software Requirements
- Python
- Jupyter Notebook
- pandas
- numpy
- Tensor flow
- PyTorch
- scikit-learn
- matplotlib
- seaborn
- Google Colab (optional)
Projects & Assessments
- Mini-projects every module (e.g., house-price predictor, customer segmentation, image classifier)
- Weekly quizzes and code reviews
- Capstone: Build & present a full AI/ML solution with real data
Outcomes
- Practical experience with core and advanced ML algorithms
- Portfolio-ready projects and a capstone showcase
- Confidence to deploy and monitor ML models in production environments
Ready to turn data into intelligent solutions?
Enroll now and start building your AI skill-set!
Instructor Information
Name:
Background:
Contact:
Office hours or discussion platform:
Java & J2EE – Full-Stack Java Developer Training
Perfect for:Beginners to intermediate learners aiming for roles in full-stack Java development.
Course Overview:
Learn Java programming from the basics to advanced enterprise development. This course covers core Java, advanced features, and server-side technologies like Servlets, JSP, Hibernate, and Spring to build real-world web applications.
Learning Outcomes
- Java fundamentals and Object-Oriented Programming
- Advanced Java concepts like collections, multithreading, and Java 8 features
- Building web applications using J2EE technologies and MVC architecture
- Working with databases using JDBC and Hibernate ORM
- Introduction to the Spring Framework for modern Java development
- Hands-on projects including Student Management and Employee Portals
Course Duration: Approximately 14–18 weeks
Format: Combination of theory, practical labs, and real-world projects
Who Should Enroll:
Aspiring Java developers, software engineers, and IT professionals aiming to master Java and enterprise application development.
Course Structure Overview
Module | Topic | Duration | Key Concepts |
1 | Core Java (Fundamentals) | 4–5 weeks | Java basics, OOP, exception handling, arrays, strings, interfaces, inner classes |
2 | Advanced Java | 3–4 weeks | Collections, generics, multithreading, file I/O, annotations, Java 8 features |
3 | J2EE (Enterprise Java) | 5–6 weeks | Servlets, JSP, JDBC, MVC, Hibernate, Spring basics, web and database integration |
4 | Hands-on Projects & Case Studies | 2–3 weeks | Real-world applications using Core Java, JDBC, JSP, Hibernate, Spring Boot |
Software Requirements:
- Java Development Kit (JDK)
- IntelliJ IDEA or Eclipse IDE
- Apache Tomcat server
- MySQL or PostgreSQL database
- Spring Boot and Hibernate frameworks
Get ready to build robust, scalable Java applications with hands-on experience and expert guidance. Join now to advance your career in Java development!
Assessment Needs
Assessment Type | Description |
Quiz | At the end of each module |
Coding Assignments | Weekly hands-on programming tasks |
Mini Projects | Small projects after Core & Advanced Java |
Final Project | Real-world application (capstone project) |
Presentation | Final project demo and explanation |
Participation | Class/lab involvement |
Course Schedule
Week | Module | Topics Covered |
1–5 | Core Java | Java basics, OOP, exception handling, strings, arrays |
6–8 | Advanced Java | Collections, generics, multithreading, Java 8+ |
9–13 | J2EE (Java EE) | Servlets, JSP, JDBC, Hibernate, Spring basics |
14–16 | Hands-on Projects | Student/Employee systems using full stack |
17–18 | Project Completion & Presentations | Final capstone project, code review, and demo |
Instructor Information
Name:
Background:
Contact:
Office hours or discussion platform:
- C Programming – From Basics to Advanced
Master the language that powers modern systems.
This hands-on course teaches foundational programming through C and advances into systemlevel concepts like memory management, data structures, and pointer manipulation.
Learning outcomes
- Core concepts: variables, control flow, arrays, strings
- Functions, recursion, and pointers
- File handling and dynamic memory allocation
- Advanced C: macros, libraries, command-line arguments
- Data structures: linked lists, stacks, queues
Perfect for:
Beginners in programming, aspiring system programmers, and engineering students.
Course Structure Overview
Module | Topic | Duration | Key Concepts |
1 | C Programming Basics | 3–4 weeks | C syntax, data types, operators, control statements |
2 | Arrays and Strings | Included above | 1D/2D arrays, string functions |
3 | Functions & Recursion | Included above | Function declaration, call by value/reference, recursion |
4 | Pointers & Memory | Included above | Pointer operations, dynamic memory allocation (malloc, calloc, free) |
5 | Structures & Unions | Included above | Creating and using user-defined data types |
6 | File I/O | Included above | Reading and writing files using fopen, fscanf, fprintf, etc. |
Assessment Needs
Assessment Type | Description |
Quizzes | Short tests after major topics |
Coding Exercises | Practice problems on logic and syntax |
Mini Assignments | Small programs (e.g., calculator, file I/O) |
Final Project | Complete C program combining key concepts |
Viva/Presentation | Oral explanation of final project |
Class Participation | Lab work and engagement |
Software Requirements
- C Compiler(e.g., GCC)
- IDE(e.g., Code::Blocks, Turbo C, Dev C++)
- Text Editor(e.g., Notepad++, VS Code)
- Terminal/Command Prompt– for compiling and running programs
- Debugger– for tracing and fixing code errors
Course Schedule
Instructor Information
Name:
Background:
Contact:
Office hours or discussion platform:
- C++ Programming – OOP and STL Mastery
Build robust, high-performance applications with modern C++.
This course covers core C++ programming concepts with a strong focus on Object-Oriented Programming (OOP), and progresses into advanced topics like templates, STL, smart pointers, and modern C++ features (C++11+).
Learning outcomes
- Classes, inheritance, polymorphism, operator overloading
- Advanced OOP: friend functions, static members, virtual functions
- Templates, exception handling, and file I/O
- STL containers: vectors, maps, sets, queues
- C++11+ features: smart pointers, lambda expressions, move semantics
Course Structure Overview
Module | Topic | Duration | Key Concepts |
1 | C++ Basics | 3–4 weeks | cin/cout, Classes Objects, Inheritance, Polymorphism, Access Specifiers |
Constructors/Destructors, Friend functions, Static members | |||
2 | Advanced C++ | 3–4 weeks | Templates, Exception Handling, File Handling, STL (Vectors, Maps, Sets, Queues) |
Smart Pointers, Lambda Expressions, Move Semantics, Rvalue References |
Assessment Needs
Assessment Type | Description |
Quizzes | Topic-wise quizzes on OOP and STL concepts |
Coding Assignments | Class-based programs, inheritance, templates |
Mini Projects | Console apps using OOP (e.g., bank system) |
Final Project | Full application using OOP + STL |
Viva/Presentation | Explain final project and logic used |
Participation | Lab activities and interactive problem solving |
Software Requirements
- C++ Compiler(e.g., GCC/G++)
- IDE(e.g., Code::Blocks, Dev C++, Visual Studio)
- Text Editor(e.g., Notepad++, VS Code)
- Debugger– for step-by-step code tracing
- Terminal/Command Prompt– to compile and run programs
Course schedule
Week | Topics Covered |
1 | Introduction to C++, I/O (cin, cout), Classes and Objects |
2 | Constructors, Destructors, Inheritance (single, multiple, multilevel, hierarchical) |
3 | Polymorphism (function/operator overloading, virtual functions), Access Specifiers |
4 | Friend Functions & Classes, Static Members |
5 | Templates (function/class), Exception Handling |
6 | File Handling (fstream, ifstream, ofstream) |
7 | Standard Template Library (STL): Vectors, Maps, Sets, Queues, Stacks |
8 | Smart Pointers, Lambda Expressions, Move Semantics |
Instructor Name
Contact Info
Certifications
Perfect for:
Programmers transitioning from C, students, and professionals building performance-critical or system-level applications.
- C# Programming with .NET
Course Overview:
This comprehensive course introduces developers to C# and the .NET framework, starting from core programming concepts to advanced development techniques. Ideal for those aiming to build desktop, web, or enterprise applications using Microsoft technologies.
Learning Outcomes:
- Master C# syntax, OOP principles, and control structures
- Work with collections, LINQ, and asynchronous programming
Module | Title | Duration | Key Topics Covered |
Module 1 | C# Basics | 3–4 weeks | Variables, Data Types, Control Flow, OOP (Classes, Objects, Inheritance, Polymorphism), Exception Handling |
Module 2 | C# Advanced | 4–5 weeks | Generics, Collections, LINQ, Async/Await, File Handling, Reflection, Events, Delegates |
- Handle errors effectively using exception handling
- Understand .NET fundamentals and advanced features like reflection and delegates
Course Structure overview
Assessment Needs
Assessment Type | Description |
Quizzes | Weekly quizzes on syntax, control flow, OOP, and advanced .NET features |
Coding Assignments | Programs using classes, LINQ, file handling, and event-driven logic |
Mini Project | Small desktop or console application using core and advanced concepts |
Final Project | End-to-end app (e.g., inventory, scheduler) using full C#/.NET stack |
Viva/Code Review | Oral explanation or walkthrough of project code |
Class Participation | Engagement in discussions, problem-solving, and practical exercises |
Course Schedule
Week | Topics Covered |
1 | Introduction to C#, Variables, Data Types, Operators, Control Structures |
2 | Methods, Arrays, Strings, and Basic Input/Output |
3 | Object-Oriented Programming: Classes, Objects, Inheritance, Polymorphism |
4 | Exception Handling, Access Modifiers, Properties |
5 | Generics, Collections (List, Dictionary), Indexers |
6 | LINQ Basics, Delegates and Events, File I/O |
7 | Asynchronous Programming (async/await), Reflection, Advanced OOP Concepts |
8 | Mini Project Development and Practice |
9 | Final Project Submission and Review |
Software Requirements:
C#, .NET Framework, Visual Studio, .NET Core/6+, LINQ
Ideal For:
Aspiring .NET developers, software engineers, and professionals transitioning to Microsoft development environments.
Assessment Needs:
- PHP Programming Course (Basic & Advanced)
Overview:
Learn PHP from the ground up, starting with basic scripting to advanced web development and database integration.
Learning Outcomes
- PHP fundamentals: syntax, variables, control flow, functions, and forms
- Object-Oriented Programming in PHP
- Database integration with MySQL (CRUD operations, prepared statements)
- Session and cookie management for user authentication
- File handling, JSON, and email sending
- Security best practices (preventing SQL injection, XSS, CSRF)
- Building web applications using MVC architecture
- Introduction to popular PHP frameworks like Laravel and CodeIgniter
- Creating RESTful APIs Duration: 10–13 weeks
Course Structure overview
Module | Duration | Topics Covered |
Module 1: PHP Basics | 3–4 weeks | - Introduction to PHP and installation - Variables, Data Types, Constants - Operators- Control Structures - Functions - Arrays - Forms and User Input - String handling - File handling |
Module 2: PHP Advanced | 4–5 weeks | - OOP in PHP (Classes, Inheritance, Interfaces) - MySQL Integration (CRUD, PDO) - Sessions and Cookies - File Uploads and Validation - JSON & API Integration - Error & Exception Handling - Email Handling- Web Security (SQLi, XSS, CSRF) |
Module 3: Web Development with PHP | 3–4 weeks | - MVC Architecture - PHP with HTML/CSS/JS - PHP Framework Intro (Laravel/CodeIgniter) - REST API creation and consumption |
Projects & Practical Work | Throughout | - Contact Form with Validation - User Registration/Login System - CRUD App for Blog/Product Management |
Assessment Needs
Assessment Type | Description | Weightage (Optional) |
Quizzes | Short topic-based quizzes to test understanding of syntax, concepts, and logic. | 10–15% |
Assignments | Weekly coding tasks on forms, arrays, file handling, OOP, and database CRUD. | 20% |
Mini Projects | Mid-course projects like login system or contact form to test integration skills. | 20% |
Final Project | Full-stack PHP web app (e.g., blog, product manager) demonstrating all concepts. | 30–40% |
Participation / Lab Work | Daily hands-on practice, lab submissions, and class engagement. | 10% |
Viva/Code Review | Oral or live demo of project code to test conceptual clarity. | 10% |
Course Schedule
Module | Duration | Focus Area |
Module 1: PHP Basics | 3–4 weeks | Core PHP syntax, forms, arrays, file handling |
Module 2: PHP Advanced | 4–5 weeks | OOP, MySQL integration, sessions, security, JSON |
Module 3: Web Development with PHP | 3–4 weeks | MVC structure, APIs, frontend integration, Laravel |
Projects & Practical Exercises | Ongoing | Hands-on projects to reinforce learning |
Final Project & Evaluation | Final 1 week | Full-stack PHP web app with code review |
Software Requirements:
- XAMPPor WAMP (to run PHP locally)
- VS Code(or any text/code editor)
- Web Browser(like Chrome or Firefox)
- phpMyAdmin(for managing MySQL)
- Git(optional, for version control)
- Postman(optional, for API testing)
Instructor Name
Contact Info
Certifications
Ready to build powerful web applications with PHP? Enroll now!
- Python Programming Course (Basic to Advanced)
Overview:
Learn Python programming from basics to advanced concepts, and apply your skills in real world projects.
Learning Outcomes:
- Python fundamentals: syntax, data types, control flow, functions, and collections
- Intermediate topics: modules, error handling, file operations, and OOP
- Advanced features: data handling, JSON/CSV/XML, databases, multithreading, and testing
- Practical skills: virtual environments, functional programming, and package management
- Real-world applications: web development (Flask/Django), GUI programming, and REST API
Course Structure Overview
Module | Duration | Topics Covered |
Python Basics | 3–4 weeks | - Introduction, IDE setup - Syntax, variables, data types - Control flow- Lists, Tuples, Sets, Dicts - String handling - Functions (incl. lambda) |
Intermediate Python | 3–4 weeks | - Modules & packages - Exception handling - File I/O - OOP (classes, inheritance) - Standard libraries - Comprehensions - Decorators & Generators |
Advanced Python | 4–5 weeks | - map(), filter(), reduce(), zip() - JSON, CSV, XML handling - SQLite DB- Multithreading & multiprocessing - Unit testing- pip & virtual env - Functional programming |
Real-World Applications | 2–3 weeks | - Flask/Django basics - GUI with Tkinter or PyQt - REST APIs using requests |
Assessment Needs
Module | Assessment |
Module 1: Basics | Quiz + Simple Programs |
Module 2: Intermediate | Coding Exercises + File Handling Task |
Module 3: Advanced | Mini Project (Database or Threading) |
Module 4: Projects | Final Project (Web or GUI App) |
Course Schedule Overview
Module | Duration | Focus |
Module 1: Python Basics | 3–4 weeks | Syntax, Data Types, Control Structures |
Module 2: Intermediate Python | 3–4 weeks | OOP, File Handling, Modules, Exceptions |
Module 3: Advanced Python | 4–5 weeks | Data Handling, Multithreading, Testing |
Module 4: Real-World Applications | 2–3 weeks | Web, GUI, and API Projects |
Software Requirements :
Software | Purpose |
Python (v3.8 or higher) | Core programming language |
VS Code / PyCharm / IDLE | Code editor / IDE |
pip | Package installer for Python |
Git (optional) | Version control (for projects) |
Flask / Django (optional) | Web development framework (Module 4) |
Tkinter / PyQt (optional) | GUI development toolkit |
SQLite3 | Built-in lightweight database |
Postman (optional) | API testing tool (for REST API practice) |
Instructor Name
Contact Info
Certifications
Start your Python journey and build versatile applications!
- Web Technologies Course (Basic to Advanced)
Overview:Learn how to build modern, responsive websites with essential web technologies.
Learning Outcomes:
By the end of the course, learners will be able to:
- Understand the structure of the web
- Describe how the internet and web work (HTTP, browsers, servers).
- Create structured web pages using HTML
- Use HTML tags to build page content and layout.
- Style web pages with CSS
- Apply styles using selectors, properties, and layout techniques (Flexbox, Grid).
- Add interactivity using JavaScript
- Use JavaScript to manipulate DOM elements and handle user events.
- Work with responsive web design
- Build mobile-friendly web pages using media queries and fluid layouts.
- Use developer tools and inspect/debug code
- Navigate browser dev tools for testing and debugging.
- Integrate forms and validate input
- Create and validate HTML forms with JS and HTML5 features.
- Understand client-server architecture
- Explain how front-end and back-end systems communicate.
- Use AJAX for dynamic content loading
- Fetch and update data asynchronously using JavaScript.
- Apply best practices in coding and design
- Write clean, maintainable code and apply UI/UX principles.
Course Structure overview
Module | Duration | Objective | Topics Covered |
1. HTML | 1–2 weeks | Understand webpage structure using HTML tags | Basic tags, page structure, text formatting, links, images, lists, tables, forms, semantic elements |
2. CSS | 1.5–2 weeks | Style and layout web pages | CSS syntax, selectors, box model, colors, fonts, Flexbox, Grid, responsive design, Bootstrap basics |
3. JavaScript | 2–3 weeks | Add interactivity to web pages | Variables, functions, control structures, arrays, DOM manipulation, event handling, ES6+ features |
4. Advanced JavaScript & Frameworks | 2–3 weeks | Master async programming and frontend frameworks | Async/await, AJAX, JSON, Fetch API, intro to React or Angular, components and state management |
Assessment Needs:
Assessment Type | Module(s) Covered | Purpose |
Quiz | All Modules | Test basic understanding |
Assignment | HTML, CSS, JavaScript | Practice hands-on skills |
Project | JavaScript & Frameworks | Build and demonstrate a web app |
Code Review | JavaScript & Frameworks | Check code quality and style |
Presentation | Final Project | Explain project and features |
Final Exam | Entire Course | Assess overall knowledge |
Software Requirements:
Software | Purpose |
Code Editor | Write code |
Web Browser | View webpages |
Local Server | Run backend code |
Git | Manage code files |
Course schedule Overview:
Module | Duration | Focus Area |
1. HTML | 1–2 weeks | Webpage structure & elements |
2. CSS | 1.5–2 weeks | Styling, layout, responsiveness |
3. JavaScript | 2–3 weeks | Interactivity & ES6+ features |
4. Advanced JS & Frameworks | 2–3 weeks | Async, AJAX, JSON, React/Angular |
Build dynamic, user-friendly websites from scratch with this comprehensive course!
- Adobe Creative Suite Training (Basic to Advanced)
Master industry-standard tools for graphic design, video editing, motion graphics, and UI/UX design.
Module | Learning Outcomes |
Adobe Photoshop | ✔ Understand layers, masks, and selections ✔ Edit and retouch images professionally ✔ Apply filters, effects, and text ✔ Design social media posts and visual compositions |
Adobe Illustrator | ✔ Create scalable vector graphics ✔ Design logos, icons, and illustrations ✔ Use pen tool, gradients, and custom brushes ✔ Apply effects and transformations |
Adobe InDesign | ✔ Design print-ready documents (brochures, books) ✔ Use master pages, grids, and typography effectively ✔ Create interactive PDFs and layouts |
Adobe Premiere Pro | ✔ Edit and arrange video clips ✔ Add transitions, effects, and audio tracks ✔ Perform color correction ✔ Export videos for various platforms |
Adobe After Effects | ✔ Create motion graphics and animations ✔ Add visual effects and tracking ✔ Composite multiple layers and media types ✔ Animate text and objects smoothly |
Adobe XD | ✔ Design modern UI/UX layouts ✔ Create interactive prototypes ✔ Collaborate and share designs ✔ Test navigation flows and user interactions |
Adobe Lightroom | ✔ Enhance and retouch photos ✔ Use presets and filters ✔ Batch process images ✔ Adjust exposure, color balance, and composition |
Learning outcomes
Course Structure Overview:
Module | Duration | Focus Area |
1. Adobe Photoshop | 2–3 weeks | Image editing, retouching, layers, masks, typography, color correction |
2. Adobe Illustrator | 2–3 weeks | Logos, icons, vector art, pen tools, gradients, brushes, 3D effects |
3. Adobe InDesign | 2 weeks | Layout design for magazines, brochures, books, interactive PDFs |
4. Adobe Premiere Pro | 2–3 weeks | Video editing, effects, audio, color correction, exporting |
5. Adobe After Effects | 2–3 weeks | Motion graphics, visual effects, animation, tracking, compositing |
6. Adobe XD | 1–2 weeks | UI design, prototyping, interactive flows, collaboration |
7. Adobe Lightroom | 1 week | Photo editing, presets, color correction, batch processing |
Assessment Needs:
Module | Assessment Methods |
Adobe Photoshop | ✔ Mini project: Photo retouch & poster design ✔ Quiz on tools & functions |
Adobe Illustrator | ✔ Logo or icon design project ✔ Tool identification & vector shapes quiz |
Adobe InDesign | ✔ Brochure or magazine layout assignment ✔ Typography & layout quiz |
Adobe Premiere Pro | ✔ Short video editing project ✔ Quiz on timeline, effects, transitions |
Adobe After Effects | ✔ Animation or title sequence creation ✔ Motion graphics techniques quiz |
Adobe XD | ✔ Interactive UI design prototype ✔ UX flow planning quiz |
Adobe Lightroom | ✔ Before/after image enhancement project ✔ Quiz on presets & editing tools |
Course Schedule Overview
Week | Module | Focus Area |
1–2 | Adobe Photoshop | Image editing, retouching, layers, typography |
3–4 | Adobe Illustrator | Logos, vector art, gradients, pen tools |
5 | Adobe InDesign | Print layout design (brochures, books, PDFs) |
6–7 | Adobe Premiere Pro | Video editing, transitions, audio, export |
8–9 | Adobe After Effects | Motion graphics, animation, visual effects |
10 | Adobe XD | UI/UX design, interactive prototypes |
11 | Adobe Lightroom | Photo editing, presets, color correction |
12 | Final Review & Showcase | Project presentation & portfolio compilation |
Course Schedule Overview
Module | Required Software | Notes |
Adobe Photoshop | Adobe Photoshop (latest version) | For image editing, layering, and retouching |
Adobe Illustrator | Adobe Illustrator | For vector design, logos, and illustrations |
Adobe InDesign | Adobe InDesign | For layout design (print & digital) |
Adobe Premiere Pro | Adobe Premiere Pro | For video editing and post-production |
Adobe After Effects | Adobe After Effects | For motion graphics and animation |
Adobe XD | Adobe XD | For UI/UX design and prototyping |
Adobe Lightroom | Adobe Lightroom (Classic or CC) | For photo editing and batch processing |
Software Requirements:
Device Type | ☐ Laptop ☐ Desktop ☐ Mac ☐ Windows |
Operating System | (e.g., Windows 10, macOS Ventura) |
RAM Available | (e.g., 8 GB, 16 GB) |
Storage Available | (e.g., 100 GB SSD) |
Graphics Card Details | (e.g., NVIDIA GTX 1650, 4 GB) |
Adobe Software Installed | ☐ Photoshop ☐ Illustrator ☐ InDesign ☐ Premiere Pro ☐ After Effects ☐ XD ☐ Lightroom |
Build your creative skills with hands-on projects and real-world applications!
- Front-End Technologies Training (Basic to Advanced):
The Front-End Technologies Course is designed to equip learners with the essential skills to build responsive, interactive, and visually engaging websites and web applications. This course covers core front-end development tools and techniques, starting from HTML and CSS, progressing through JavaScript, and ending with modern frameworks like React or Angular
Learning Outcomes:
By the end of this course, students will be able to:
- Build and style fully functional web pages using HTML and CSS.
- Make web pages interactive with JavaScript.
- Understand and apply modern JavaScript features (ES6+).
- Develop dynamic, responsive front-end interfaces using frameworks.
- Prepare for real-world front-end development roles or freelance projects.
Course Structure Overview
Module | Duration | Key Topics |
3. JavaScript Basics | 2–3 weeks | Variables, functions, loops, events, DOM, ES6+, JSON |
4. Advanced JavaScript | 2–3 weeks | Async programming, APIs, modules, debugging, code structure |
5. React.js | 4–5 weeks | Components, hooks, routing, state management, deployment |
6. Version Control & Tooling | 1 week | Git, GitHub, npm, Webpack, Babel, CLI basics |
7. UI Frameworks & Tools | 1–2 weeks | Bootstrap, Tailwind CSS, Material UI, Figma |
8. Testing & Deployment | 1 week | Testing with Jest, responsiveness, deployment (GitHub Pages, Vercel, Netlify) |
Assessment Needs
Assessment Type | Description |
Quizzes | Short tests after each module (HTML, CSS, JS, etc.) |
Assignments | Practice tasks like building forms, styling pages, or scripting interactions |
Mini Projects | Small websites or components (e.g., portfolio, landing page) |
Capstone Project | Final comprehensive website or app using HTML, CSS, JavaScript, and framework |
Presentation/Demo | Students present their final project and explain features |
Class Participation | Regular coding practice, discussion, and question-answer sessions |
Course Schedule Overview
Module | Duration | What You Learn |
1. HTML | 1–2 weeks | Webpage structure, forms, tables, media, semantic tags |
2. CSS | 1.5–2 weeks | Styling, layout, colors, fonts, Flexbox, Grid, Bootstrap |
3. JavaScript | 2–3 weeks | Interactivity, DOM, events, ES6 features |
4. Advanced JavaScript & Frameworks | 2–3 weeks | AJAX, JSON, async programming, intro to React/Angular |
Software Requirements:
- VS Code– To write code
- Google Chrome / Firefox– To check how your website looks
- js + npm– To run JavaScript tools
- Git– To track changes in your code
- GitHub– To store and share your projects
- Figma– To design web page layouts
- Live Server (VS Code extension)– To preview your web pages live
- React Developer Tools– To debug React apps (browser extension)
- Postman– To test APIs (optional)
- Jest– To test your JavaScript code (optional)
Build dynamic, user-friendly websites and apps with hands-on projects throughout the course!!!
- Full Stack Development Training (Basic to Advanced)
Learn to build complete web applications by mastering front-end (HTML, CSS, JavaScript, React), back-end (Node.js, Express), databases (MongoDB, SQL), and deployment. Gain skills in security, version control, testing, and launching real projects.
Course Structure Overview
Module | Title | Duration | Key Topics Covered |
1 | Web Development Foundations | 2–3 weeks | HTML5, CSS3, JavaScript basics, responsive design, CSS frameworks (e.g., Bootstrap), Git basics |
2 | Advanced JavaScript | 2 weeks | ES6+ features, asynchronous programming (Promises, async/await), DOM manipulation, REST APIs, browser storage |
3 | Frontend Development with React | 4 weeks | React components, hooks, props/state, routing (React Router), state management (useContext/Redux), app deployment |
4 | Backend Development with Node.js & Express | 3–4 weeks | Express.js server setup, RESTful APIs, middleware, routing, request handling, error handling, integration with frontend |
5 | Database Management | 2–3 weeks | MongoDB (NoSQL) or MySQL (SQL), CRUD operations, schema design, data modeling |
6 | Authentication & Authorization | 1.5 weeks | User registration/login, password hashing (bcrypt), JWT authentication, role-based access, protected routes |
7 | Deployment & DevOps Basics | 1 week | Deployment strategies, GitHub Actions, CI/CD basics, domain setup, SSL, hosting platforms (Vercel, Netlify, Heroku, etc.) |
8 | APIs & External Services | 1–2 weeks | Consuming/building REST APIs, Postman testing, file uploads, email integration, third-party services, basics of real-time (WebSockets) |
Topic | Assessment |
HTML & CSS | Small web page creation, quizzes |
JavaScript | Code exercises, logic tests |
React.js | Build a simple app with components |
Node.js & Express | Create and test a basic API |
Databases | Perform CRUD operations |
Git & GitHub | Push code to GitHub, version control tasks |
UI Tools (Bootstrap) | Apply styling to a sample project |
Testing | Write basic unit tests |
Deployment | Deploy an app on GitHub Pages or Netlify |
Final Project | Complete a full stack mini application |
Assessment Needs
Week | Focus | Activities |
1–4 | Front-End Fundamentals | HTML, CSS, JavaScript basics |
5–8 | Advanced Front-End & React | React, Hooks, Routing |
9–12 | Back-End & APIs | Node.js, Express, RESTful services |
13–15 | Database Integration | MongoDB/SQL, CRUD operations |
16–17 | Authentication & Security | JWT, sessions, secure login |
18–19 | Deployment & DevOps | Git workflows, CI/CD, cloud deployment |
20–21 | Testing & Optimization | Jest, debugging, performance |
22–24 | Capstone Project | Full-stack app development & presentation |
Course Schedule Overview
Software Requirements:
- VS Code(Code Editor)
- Google Chrome / Firefox(Browser)
- js & npm(Backend runtime & package manager)
- Git & GitHub(Version control & repository)
- MongoDB Atlas / MySQL(Databases)
- Postman(API testing)
- Docker(Optional, for containerization)
- Heroku / Netlify / AWS(Hosting platforms)
Instructor Name
Contact Info
Certifications
Master front-end and back-end skills.Start your journey to becoming a full stack developer!!!!
Cyber Security Professional Program
Overview:
This comprehensive 20-module course provides hands-on training in ethical hacking, network defense, malware analysis, cloud and IoT security, and cryptography. Designed for aspiring cybersecurity professionals, the program combines theoretical knowledge with practical labs and real-world simulations.
Learning Outcomes
- Core cybersecurity principles (CIA triad, NIST, ISO)
- Network scanning, system hacking, and vulnerability assessment
- Web and mobile security, DoS attacks, wireless and cloud security
- Social engineering, IoT protection, and cryptographic techniques
- Full-scope penetration testing with industry tools like Nmap, Nessus, Burp Suite, and Metasploit
Course Structure Overview:
Module | Title | Key Topics Covered |
1 | Introduction to Cybersecurity | Cybersecurity basics, its importance |
2 | Networking Fundamentals | Networks, OSI/TCP-IP Models, IPv4/IPv6, Subnetting |
3 | Linux Fundamentals | Linux OS, Shell, File System, CLI Commands |
4 | Ethical Hacking Basics | Security elements, hacking phases, types of hackers/attacks |
5 | Footprinting & Reconnaissance | Techniques for info gathering, DNS, domain enumeration |
6 | Scanning and Enumeration | Nmap, ports/services, scanning types |
7 | System Hacking | Password attacks, hash cracking, keyloggers |
8 | Malware Threats | Viruses, worms, malware introduction |
9 | Network Attacks | Sniffing, MITM, MAC spoofing, Wireshark basics |
10 | Social Engineering | Human-based attacks, phases, DoS/DDoS concepts |
11 | Denial-of-Service Attacks | DoS/DDoS mechanisms |
12 | Honeypots | Honeypot use, setup, and configuration |
13 | Hacking Web Servers | OWASP Top 10, SQL injection, CSRF, XSS, brute force |
14 | Hacking Wireless Networks | Wireless security, WEP/WPA, spoofing, WPA2 attacks |
15 | Cryptography Basics | Types, ciphers, tools used in encryption |
Assessment Needs:
Module | Assessment |
Introduction to Cybersecurity | Quiz |
Networking Fundamentals | Quiz, Diagram |
Linux Fundamentals | Hands-on CLI Practice |
Ethical Hacking Introduction | Quiz, Scenarios |
Footprinting & Reconnaissance | Lab Activity |
Scanning & Enumeration | Nmap Practical |
System Hacking | Password Cracking Task |
Malware Threats | MCQs, Tool Review |
Network Attacks | Wireshark Lab |
Social Engineering | Quiz, Role Play |
Denial-of-Service Attacks | Simulation/Diagram |
Honeypots | Setup & Report |
Hacking Web Servers | Vulnerability Lab |
Hacking Wireless Networks | Wireless Attack Demo |
Cryptography Basics | Quiz, Cipher Task |
Software Requirements:
Software/Tool | Purpose |
Kali Linux / Parrot OS | Ethical hacking & penetration testing |
VirtualBox / VMware | Running virtual machines safely |
Wireshark | Network traffic monitoring and analysis |
Nmap | Network scanning and enumeration |
Burp Suite / OWASP ZAP | Web application security testing |
John the Ripper | Password cracking |
Hashcat | Advanced hash cracking |
VS Code / Notepad | Code and script editing |
Firefox / Chrome | Secure web browsing and testing |
Course Schedule Overview
Week | Module | Topics Covered |
Week 1 | Introduction to Cybersecurity | Basics, Importance of Cybersecurity |
Week 2 | Networking Fundamentals | Networks, OSI/TCP-IP Models, Subnetting |
Week 3 | Linux Fundamentals | Linux CLI, File System, Commands |
Week 4 | Ethical Hacking Basics | Hacking Phases, Attack Types |
Week 5 | Footprinting & Reconnaissance | Info Gathering, DNS, Tools |
Week 6 | Scanning & Enumeration | Nmap, Ports, Enumeration Techniques |
Week 7 | System Hacking | Password Cracking, Keyloggers |
Week 8 | Malware Threats | Types of Malware, Virus, Worms |
Week 9 | Network Attacks | Sniffing, MITM, MAC Spoofing |
Week 10 | Social Engineering & DoS Attacks | Phishing, DDoS Methods |
Week 11 | Honeypots | Setup, Use in Security |
Week 12 | Web Server Hacking | OWASP Top 10, SQLi, XSS |
Week 13 | Wireless Hacking | WPA2, WEP, Wireless Tools |
Week 14 | Cryptography Basics | Ciphers, Hashing, Encryption Tools |
Format:
20-week structure, with one module per week. Includes downloadable resources, video tutorials, and support from certified instructors.
Ideal for:
Beginners to intermediate learners, IT professionals, and students preparing for roles like Security Analyst, Pen Tester, or SOC Analyst.
"Be the shield. Master Cybersecurity today!"
Instructor Name
Contact Info
Certifications
Timings
SCCM 2007 / 2010 – Condensed (Basic to Advanced):
Course Overview:
This SCCM (System Center Configuration Manager) course provides a comprehensive guide from basic setup to advanced deployment techniques. You'll learn how to install and configure SCCM 2007/2010, manage clients, deploy software and operating systems, enforce security, and generate reports. Ideal for IT professionals aiming to streamline enterprise system management and automate administrative tasks efficiently.
Learning Outcomes:
1 | Understand SCCM architecture, components, and version differences. |
2 | Install SCCM with all prerequisites and configure site roles. |
3 | Deploy and manage SCCM clients using different methods. |
4 | Collect and analyze hardware and software inventory. |
5 | Create, deploy, and monitor applications, packages, and patches. |
6 | Configure Windows updates using WSUS and SUP. |
7 | Set up and troubleshoot Operating System Deployment (OSD). |
8 | Use USMT to migrate user data during OS upgrades. |
9 | Configure Endpoint Protection and compliance settings. |
10 | Use SCCM reporting tools like SSRS and built-in reports. |
11 | Manage backup, recovery, and SCCM migrations. |
Course Structure Overview:
Module | Topics Covered |
1. SCCM Overview & Installation | - SCCM architecture and components - Differences between 2007 & 2010 - Prerequisites (SQL, AD, WSUS, IIS) - Installation & site roles - Boundaries & discovery methods |
2. Client Management | - Client deployment methods (manual, push, GPO) - Client health & troubleshooting - Hardware/software inventory - Important log files & tools |
3. Software & Patch Deployment | - Application vs Package model - Creating & deploying software - Integrating Windows Updates (WSUS, SUP) - Using Automatic Deployment Rules (ADR) - Monitoring and reporting deployments |
4. Operating System Deployment (OSD) | - Boot images & task sequences - PXE boot setup - Capturing/deploying OS images - Using USMT for data migration - Troubleshooting OSD issues |
5. Security, Reporting & Administration | - Endpoint Protection setup - Compliance settings & baselines - Role-Based Access Control (RBAC) - Reporting (SSRS & built-in) - Backup, recovery & migration best practices |
Assessment Needs:
Module | Assessment Type | Description |
Module 1: Overview & Installation | Quiz | Test on SCCM basics and installation |
Module 2: Client Management | Practical Task | Deploy clients and troubleshoot |
Module 3: Software & Patch Deployment | Hands-on Assignment | Create and deploy software packages |
Module 4: Operating System Deployment | Practical Exercise | Capture and deploy OS images |
Module 5: Security & Reporting | Configuration Task + Report Review | Setup security settings and generate reports |
Final Assessment | Quiz + Project | Comprehensive test and practical project |
Software Requirements
Software | Purpose |
Windows Server | SCCM server installation |
SQL Server | Database for SCCM |
Active Directory | User and computer management |
WSUS | Windows update services |
IIS (Internet Info Svcs) | Web services for SCCM |
SCCM 2007 or 2010 | Configuration Manager software |
Client OS (Windows 7/10) | For deploying and managing clients |
Course Schedule Overview
Week | Module | Assessment Type | Key Activities |
Week 1 | Module 1: Overview & Installation | Quiz | Learn SCCM basics and installation concepts; complete quiz |
Week 2 | Module 2: Client Management | Practical Task | Deploy SCCM clients, troubleshoot client issues |
Week 3 | Module 3: Software & Patch Deployment | Hands-on Assignment | Create software packages, deploy patches |
Week 4 | Module 4: Operating System Deployment | Practical Exercise | Capture OS images and deploy to clients |
Week 5 | Module 5: Security & Reporting | Configuration Task + Report Review | Configure security settings; generate and review reports |
Week 6 | Final Assessment | Quiz + Project | Comprehensive written test and practical project |
Instructor Name
Contact Info
Certifications
Timings
“Master SCCM: Deploy, Manage, Secure — Your Path to IT Excellence”!!!!
Curriculum
- 0m Duration