ATLAS SkillTech University: India's 1st Urban Multidisciplinary University ATLAS SkillTech University

Program Essence

This program is a transformative journey into the world of Generative AI and Agentic AI, equipping learners with both the theoretical foundations and practical expertise to create, manage, and optimize AI systems that think, generate, and act autonomously. Over three months, participants will develop a deep understanding of AI-driven creativity, decision-making, and agentic intelligence, preparing them to lead AI initiatives across industries.

What You’ll Learn

Generative AI Mastery

Understand the core principles behind text, image, and multimodal AI generation

Agentic AI & Autonomous Systems

Learn to design AI agents that can plan, act, and make decisions independently

Practical AI Implementation

Hands-on experience in building, fine-tuning, and deploying AI models for real-world problems

Ethical & Responsible AI

Understand the ethical, legal, and societal implications of AI systems

AI Product & Solution Design

Translate AI capabilities into impactful products and services

Future Trends in AI

Explore emerging paradigms like AI orchestration, self-improving agents, and human-AI collaboration

Why Choose This Program?

Hands-On, Industry-Aligned Learning

Work on real-world projects and gain experience with cutting-edge AI tools

01

Expert Faculty & Mentors

Learn from AI practitioners and researchers driving innovation globally

02

Future-Proof Skillset

Gain skills in the most transformative AI technologies shaping the future of work and society

03

Capstone Showcase & Career Support

Demonstrate your expertise and get guidance to land AI-driven roles or launch AI ventures

04

Networking Opportunities

Engage with peers, mentors, and leading practitioners in the wealth management field

05

A Curriculum Designed for the Future

Built on the ‘Goal for Each Term’ (GET) philosophy, our curriculum ensures every semester has a clear, outcome-driven focus; continuously evolving with emerging technology trends and the learning needs of our students.

Semester 1

Become a Game Developer

This semester introduces the foundational principles of programming, mathematics, and digital communication essential for aspiring game developers. Students build analytical skills, explore computation, and begin creative problem-solving through simulation and game design.

Introduction to Computer Science & Programming 1

Provides a hands-on introduction to computational thinking and programming fundamentals.

Calculus 1

Introduces foundational mathematical concepts and techniques for modeling and problem-solving in AI and design.

Foundations of Statistics & Probability for AI & ML

Covers statistical reasoning and probabilistic methods essential for machine learning and AI applications.

Databases & SQL

Teaches principles of database design, querying, and management using SQL for data-driven projects.

Chemistry

Explores basic chemical principles and their applications in technology, materials, and interactive systems.

Communication Skills for Digital World

Enhances written and verbal communication tailored for digital, academic, and professional contexts.

ATLAS Electives

Offers interdisciplinary elective courses that combine technology, design, and creative innovation.

Simulation/Computer Game Design (Pinnacle I)

Develops computational design skills through interactive simulations blending programming, logic, and visual storytelling.

Semester 2

Become a Data Analyst

This semester strengthens computational, mathematical, and analytical thinking skills essential for data-driven decision-making. Students explore algorithms, modeling, and applied projects that bridge science, programming, and real-world data interpretation.

Introduction to Computer Science and Programming 2

Advances coding proficiency through structured programming, data types, and modular problem-solving.

Mathematics for Computer Science

Explores discrete mathematics, logic, and combinatorics vital for computational systems design.

Calculus 2

Extends integral and differential calculus applications in modeling and engineering systems.

Physics

Covers mechanics, electromagnetism, and thermodynamics to strengthen scientific grounding in computational systems.

Statistical Modeling

Focuses on building and interpreting predictive models using regression and probabilistic analysis.

Indian Health Sciences

Examines traditional health knowledge systems and their relation to technology, ethics, and data innovation.

Expository Writing

Develops clarity, structure, and critical reasoning in technical and analytical writing.

ATLAS Electives

Offers cross-domain learning to build interdisciplinary competence and creativity.

Data Analyst Project (Pinnacle II)

Applies statistical and computational techniques to analyze real datasets and visualize insights.

Semester 3

Become a Data Scientist

This semester delves into the computational and mathematical core of data science, emphasizing machine learning, data structures, and large-scale storage systems. Students build a strong foundation in algorithmic thinking and learn to derive insights from structured and unstructured data through practical, interdisciplinary applications.

Machine Learning Foundations

Covers supervised and unsupervised learning algorithms, model training, and evaluation techniques.

Computer Organization and Architecture

Explores system architecture, hardware components, and memory organization for computational efficiency.

Linear Algebra

Builds conceptual understanding of matrices, vectors, and transformations used in machine learning.

Data Structures

Introduces efficient data storage, manipulation, and algorithm optimization for problem-solving.

Unstructured Data, NoSQL, and Storage Techniques

Focuses on handling big data using NoSQL databases and distributed storage solutions.

Model Thinking

Applies mathematical and conceptual models to understand patterns in data and complex systems.

Foundational Literature of Indian Civilization

Examines Indian philosophical, cultural, and intellectual traditions with modern contextual relevance.

ATLAS Electives

Applies machine learning to advanced scientific domains through real-world research projects.

Machine Learning: Astrophysics, Particles, Drug Design (Pinnacle III)

Applies machine learning to advanced scientific domains through real-world research projects.

Semester 4

Become an ML Engineer

This semester advances machine learning mastery with a focus on scalable systems, algorithms, and automated data operations. Students gain hands-on experience integrating DevOps and MLOps practices while developing enterprise-level AI solutions that address real-world business and technological challenges.

Advanced Machine Learning

Explores deep neural networks, reinforcement learning, and optimization techniques for complex AI systems.

Introduction to Algorithms

Builds understanding of algorithmic logic, efficiency, and problem-solving strategies in computing.

Operating Systems and Networks

Covers fundamentals of OS architecture, process management, and computer networking protocols.

Large-Scale Data Storage

Teaches distributed databases, cloud storage, and scalable data management techniques.

Software Development Lifecycle, DevOps and MLOps

Integrates DevOps practices into ML workflows to enhance deployment and reliability.

Data Engineering Operations

Focuses on pipeline automation, data cleaning, and transformation for ML readiness.

Business Plan Writing

Develops entrepreneurial thinking through strategic, financial, and innovation-driven project planning.

ATLAS Electives

Encourages multidisciplinary exploration to expand creative and technical skill sets.

An Enterprise Grade AI Application: Recommendation Engines for OTT Platforms (Pinnacle IV)

Applies ML algorithms to build intelligent recommendation systems for personalized media platforms.

Semester 5

Become a Digital Technology Engineer

This semester integrates AI, cloud systems, and digital innovation to prepare students for high-impact engineering roles. Learners explore intelligent automation, entrepreneurship, and modern computing applications, culminating in the design of connected autonomous systems using deep learning and real-world data.

Reinforcement Learning and NLP

Master the art of making big-picture decisions. Learn how to evaluate competition, allocate resources, and plan for long-term business success in volatile environments.

Computer Vision and Deep Learning

Focuses on enabling machines to interpret and process visual information from the world.

Advanced Algorithms

Develops efficiency and complexity analysis skills for solving high-level computational problems.

Emerging Technologies

Explores next-gen digital trends like IoT, quantum computing, and immersive tech ecosystems.

Cloud Application Development

Explores cloud infrastructure, APIs, and deployment pipelines for scalable AI-based applications.

Entrepreneurship Development

Encourages innovation through idea validation, resource planning, and tech-based business creation.

Academic Research Writing

Builds research methodologies and technical writing skills for academic and industrial use.

Enterprise Grade Connected Device Application: Self-Driving Cars (Pinnacle V)

Applies AI, robotics, and cloud systems to develop functional models for autonomous vehicles.

Semester 6

Become a Cyber Security Engineer

This semester focuses on building expertise in system security, blockchain, and ethical coding. Students gain the ability to develop, optimize, and secure digital systems through encryption techniques, AI integration, and real-world cybersecurity practices. It combines advanced coding, data protection, and digital literacy to create future-ready security professionals.

Secure Coding

Emphasizes writing robust code that prevents vulnerabilities, exploits, and data breaches.

Project Life Cycle Management

Covers planning, execution, and evaluation stages in engineering and software projects.

Numeric Optimization Techniques

Teaches mathematical optimization methods used in algorithms, AI, and data modeling.

Recent Advances and Challenges in AI

Explores breakthroughs in AI technologies with focus on ethics and implementation barriers.

UI/UX Development

Introduces principles of user-centered design for intuitive digital interfaces and systems.

Cybersecurity and Blockchain

Explains cryptographic systems, network defense, and blockchain’s role in secure transactions.

Digital Culture and Language

Examines the intersection of digital communication, societal change, and global connectivity.

Build Your Own Encryption Software (Pinnacle VI)

Applies cryptographic principles to design and deploy a custom encryption solution.

Semester 7

Become an AI Entrepreneur

This semester empowers students to merge artificial intelligence with innovation and entrepreneurship. It builds advanced technical, ethical, and strategic skills to develop AI-driven products, protect digital assets, and manage security challenges — preparing students to lead startups in the intelligent automation era.

AI in Engineering

Applies artificial intelligence to solve complex engineering challenges and optimize design processes.

Network Security

Covers secure networking principles, cryptographic methods, and protection against cyber threats.

Knowledge Graphs and Minor Project

Introduces semantic data modeling to build intelligent systems through connected knowledge structures.

Prompt Engineering

Focuses on designing effective AI prompts for optimal model performance and interaction outcomes.

Agentic AI

Explores autonomous AI agents capable of dynamic reasoning, decision-making, and multi-task execution.

Ethical Hacking

Teaches penetration testing, vulnerability assessment, and ethical approaches to cybersecurity.

Intellectual Property and Innovation in AI

Examines patent law, copyright, and intellectual property rights within AI-based innovation ecosystems.

Constitution of India

Promotes understanding of constitutional values, justice, and legal frameworks in technological development.

Semester 8

Internship and Project

This final semester emphasizes applied learning through research, innovation, and professional execution. Students synthesize their AI and engineering expertise into a product-based dissertation while gaining real-world exposure to human-centered design and accelerated AI development.

Internship and Project and Dissertation (Product Based)

Applies AI and data science principles to develop, test, and deploy real-world product solutions.

Federated Learning and Distributed AI (MOOC)

Explores decentralized machine learning frameworks enabling collaborative intelligence while preserving data privacy.

Cognitive Systems and Human-AI Interaction (MOOC)

Studies intelligent systems that interpret, adapt, and respond to human behavior for seamless AI collaboration.

> Tech Professionals: Developers, engineers, and data scientists aiming to specialize in AI innovation

> Business Leaders & Innovators: Entrepreneurs, product managers, and strategists seeking to leverage AI for competitive advantage

> AI Enthusiasts & Students: Individuals with a basic understanding of AI who want a structured, hands-on learning journey

Generative & Agentic AI

Program USP's

Program Essence

What You’ll Learn

Why Choose This Program?

Hands-On, Industry-Aligned Learning

Expert Faculty & Mentors

Future-Proof Skillset

Capstone Showcase & Career Support

Networking Opportunities

A Curriculum Designed for the Future

Semester 1

Introduction to Computer Science & Programming 1

Calculus 1

Foundations of Statistics & Probability for AI & ML

Databases & SQL

Chemistry

Communication Skills for Digital World

ATLAS Electives

Simulation/Computer Game Design (Pinnacle I)

Semester 2

Introduction to Computer Science and Programming 2

Mathematics for Computer Science

Calculus 2

Physics

Statistical Modeling

Indian Health Sciences

Expository Writing

ATLAS Electives

Data Analyst Project (Pinnacle II)

Semester 3

Machine Learning Foundations

Computer Organization and Architecture

Linear Algebra

Data Structures

Unstructured Data, NoSQL, and Storage Techniques

Model Thinking

Foundational Literature of Indian Civilization

ATLAS Electives

Machine Learning: Astrophysics, Particles, Drug Design (Pinnacle III)

Semester 4

Advanced Machine Learning

Introduction to Algorithms

Operating Systems and Networks

Large-Scale Data Storage

Software Development Lifecycle, DevOps and MLOps

Data Engineering Operations

Business Plan Writing

ATLAS Electives

An Enterprise Grade AI Application: Recommendation Engines for OTT Platforms (Pinnacle IV)

Semester 5

Reinforcement Learning and NLP

Computer Vision and Deep Learning

Advanced Algorithms

Emerging Technologies

Cloud Application Development

Entrepreneurship Development

Academic Research Writing

Enterprise Grade Connected Device Application: Self-Driving Cars (Pinnacle V)

Semester 6

Secure Coding

Project Life Cycle Management

Numeric Optimization Techniques

Recent Advances and Challenges in AI

UI/UX Development

Cybersecurity and Blockchain

Digital Culture and Language

Build Your Own Encryption Software (Pinnacle VI)

Semester 7

AI in Engineering

Network Security

Knowledge Graphs and Minor Project

Prompt Engineering

Agentic AI

Ethical Hacking

Intellectual Property and Innovation in AI

Constitution of India

Semester 8

Internship and Project and Dissertation (Product Based)

Federated Learning and Distributed AI (MOOC)