Key Responsibilities
- Deliver engaging classroom and practical training sessions for trainees.
- Train students on Python programming, Data Science, Machine Learning, and AI fundamentals.
- Conduct hands-on lab sessions, coding exercises, and real-time project guidance.
- Design training materials, assignments, assessments, and project modules.
- Guide trainees in model building, testing, debugging, and deployment basics.
- Monitor trainee performance and provide continuous mentoring and feedback.
- Handle technical lab setup and support during practical sessions.
- Stay updated with the latest AI tools, frameworks, and industry trends.
Technical Skills Required
Core Technical Proficiency
- Strong knowledge of Python Programming
- Statistics & Data Analysis
- NumPy, Pandas, Matplotlib
- Machine Learning Algorithms
- Deep Learning Basics
- NLP & OpenCV
- TensorFlow / Keras Basics
- AI Tools & Prompt Engineering
- Model Training & Deployment Basics
Software & Tools Knowledge
Trainer should be proficient in:
- Jupyter Notebook / Google Colab
- VS Code / PyCharm
- Python Libraries & Frameworks
- AI Tools such as ChatGPT, Gemini, GitHub Copilot, etc.
- Excel & Data Visualization Tools
Practical & Training Skills
The candidate should have hands-on experience in:
- Dataset handling and preprocessing
- Model building and testing
- Debugging Python code
- AI project implementation
- Conducting practical lab sessions
- Managing trainee projects and assignments
Qualification Required (any one):
MCA / DOEACC B-Level / B.E. / B.Tech (CS/CE/IT) / M.Sc (CS/IT) or equivalent with minimum 1+ year experience
BCA / DOEACC IT-A Level / PGDCA or equivalent with minimum 2+ years experience
M.Tech / M.E. (Computer Science or IT) or equivalent from a recognized university/institute
Experience Required:
Minimum 2 years teaching experience in the relevant course