The course features a hands-on full-stack capstone, building and refactoring Django applications end-to-end.
From implementing MySQL models, to RESTful API endpoints, and form-driven pages, paired with responsive HTML/CSS/JavaScript UIs, the course
covered core full-stack concepts and deployment environments while delivering a production-style app.
The course features a hands-on course covering REST fundamentals, HTTP workflows, serialization, routing, and basic authentication. Work includes building Django-based API backbones with CRUD endpoints, testing and optimizing performance, and producing developer-ready documentation, with exposure to emerging API technologies and design patterns.
A hands-on course on building, securing, and administering web apps with Django. Topics include app architecture (models, views, templates, and URL routing), the HTTP request–response cycle, ORM data modeling, dynamic forms and validation, the Django Template Language, admin customization, and security hardening (authentication, CSRF, permissions). Emphasis is placed on deployment and testing best practices.
The course provides a practical introduction to Git and GitHub, covering version control fundamentals, branching and merging, conflict resolution, and history inspection for debugging and recovery. It also walks through configuring remotes and collaborating via GitHub—forks, pull requests, code reviews, and issues the aids in managing team workflows and publish a professional portfolio.
A practical, task-focused course on automating everyday workflows with Python. It covers file system operations and batch renaming, CSV/Excel processing, text parsing (including regex), command-line scripting with argparse, robust error handling/logging, web scraping with Requests/BeautifulSoup, browser automation with Selenium, and working with APIs.
A hands-on course focused on building and evaluating models in Python using scikit-learn and Jupyter. Covers regression (linear, multiple, polynomial, logistic), supervised learning (decision trees, k-NN, SVM), and unsupervised techniques (clustering) plus dimensionality reduction (PCA, t-SNE, UMAP). Emphasizes data preparation, metrics, cross-validation, regularization, and pipeline optimization, culminating in a rainfall-prediction project and exam.
A practical course on mobile robot navigation in ROS that bridges core theory with implementation.
It focuses on the tf transform system—frames, transforms, and timing—and shows how
localization, mapping, and planning concepts map onto ROS navigation components.
tf package to manage frames, transforms, and time across a robot stack.
The course features a hands-on introduction to ROS covering core middleware (nodes, topics, services, messages), motion control and kinematics for mobile robots (pose representation and linear/rotational/spiral trajectories), and perception pipelines using camera input with OpenCV. It concludes with Arduino integration via rosserial for sensor/actuator interfacing, emphasizing how to build, launch, and debug end-to-end ROS applications.
Covers the foundations of autonomous mobile robots, including locomotion and kinematics, environment perception, probabilistic localization and mapping (SLAM), and motion planning. Exercises span wheeled, legged, and aerial platforms, translating core theory into implementable algorithms. Based on Introduction to Autonomous Mobile Robots (Siegwart, Nourbakhsh, Scaramuzza; 2nd ed., MIT Press).
Hands-on introduction to building practical IoT devices with Raspberry Pi. Starting with setting up the environment, installing and running a Linux OS, writing and executing Python on-device, working with Python-based IDEs, and practicing tracing/debugging.