The Python Programming course develops a structured foundation across four source-defined units. Learners begin with python basics, progress to decision making in python, loops, tracing, debugging, and repeated logic, then move into strings and lists, tuples, sets, dictionaries, and choosing the right structure, and close with functions, modules, exceptions, files, and mini project. The sequence is supported by theory sessions, course materials, code practice and practice codes, helping learners connect each unit with a consistent learning rhythm.
The curriculum moves from Python basics and decision logic to core collections, then closes with functions, modules, exceptions, files and a source-defined mini project. Designed for students, technical learners and early-career professionals, the course provides a focused six-week online pathway that preserves the supplied module order and topic pattern. The emphasis remains on the skills and concepts named in the source curriculum, with no unsupported modules, tools or outcomes added.
Build practical Python foundations through structured coding and debugging practice
The project submission process helps learners apply Generative AI concepts in a practical and structured way. Therefore, participants complete project work to demonstrate their understanding, originality, and professional application.
First, explore the project topics available in the LMS. Review the project description, learning outcomes, and required skills before selecting your topic.
If required, ask your guide or mentor for support. After that, finalize your topic and begin your project work.
Once your project report is complete, follow the project submission guidelines for formatting, font, spacing, citations, and originality.
Your report will go through a plagiarism check. Therefore, keep the work original, properly structured, and clearly written.
Finally, upload your final PDF report and any supporting files to the LMS.
After submission, your project is evaluated by an organization mentor and an internal faculty supervisor.
The evaluation focuses on report quality, depth of understanding, concept application, problem-solving skills, professional behaviour, and timely submission. In some cases, a viva or presentation may also be required.
Credits may be awarded as per applicable UGC NEP 2020 guidelines. In addition, your internship certificate will be issued after report approval, evaluation completion, and uploading of the required organization certificate.
Thereafter, learners can download the internship completion certificate directly from the LMS.
