Learning Path

Module 1

This unit introduces learners to Python programming and computational thinking. Students will learn coding fundamentals, control structures, functions, and data structures through hands-on practice. The module also focuses on algorithmic problem-solving, debugging, and real-world application development using Python.

Module 2

This unit covers the fundamentals of data science, statistics, and data visualization techniques. Learners will work with tools such as NumPy, Pandas, Matplotlib, and Seaborn for data analysis and preprocessing. The module also introduces statistical methods, probability concepts, and dashboard creation for data-driven decision-making.

Module 3

This unit focuses on advanced machine learning concepts and practical model development. Students will learn supervised and unsupervised learning, feature engineering, ensemble techniques, and model evaluation. The module also includes hands-on implementation and deployment of ML models using modern tools and frameworks.

Module 4

This unit introduces the core principles of Artificial Intelligence and Machine Learning. Learners will explore search algorithms, classification, clustering, and neural networks through practical sessions. The module builds a strong foundation for designing intelligent systems and AI-driven applications.

Module 5

This unit provides in-depth exposure to deep learning and advanced AI technologies. Students will work with TensorFlow and PyTorch to build CNNs, RNNs, GANs, and reinforcement learning models. The module emphasizes real-world AI applications, model optimization, and intelligent solution development.

Module 6

This unit introduces cloud computing concepts and application deployment using AWS. Learners will gain practical exposure to cloud infrastructure, storage, networking, automation, and CI/CD pipelines. The module prepares students to deploy scalable and secure AI/ML solutions in cloud environments.

Module 7

This unit focuses on industry readiness through specialized add-on courses, capstone projects, and internship opportunities. Students will work on real-world projects under expert mentorship while improving communication, teamwork, and presentation skills. The internship component provides practical industry exposure and placement-oriented experience.

Tools Covered

Scholarship Test

Admission Process

Admission to the program will be based on an Assessment Test and a Personal Interview conducted to understand the candidate’s aptitude, interest, and commitment towards the program.

As the program is fully sponsored by the Scheduled Tribes Development Department and seats are limited, admission will be offered to eligible and genuinely interested candidates based on their overall performance in the assessment process.

Elgibility

The program is open to ST community youth who meet the following criteria:

Engineering or science graduates, or those with a three-year diploma in any engineering branch, with foundational knowledge in Mathematics and Computer Fundamentals (equivalent to Plus Two).
Students who have completed their graduation but are awaiting final results may also apply.

*Please note, the ICT Academy of Kerala reserves the right to cancel the candidature if found ineligible at any point.