In an increasingly digital world, cybersecurity threats and AI-driven innovations are reshaping industries at breakneck speed. This three-month intensive program equips professionals and enthusiasts with the skills to safeguard digital landscapes while leveraging AI to drive intelligent solutions. Through a blend of theoretical foundations and hands-on projects, participants will emerge as future-ready experts capable of navigating the intersection of cybersecurity and artificial intelligence.
What You’ll Learn
Fundamentals of Cybersecurity
risk assessment, threat detection, cryptography, and incident response
Core AI & Machine Learning concepts
neural networks, NLP, computer vision, and predictive modelling
Integration of AI in Cybersecurity
threat intelligence, anomaly detection, automated defence systems
Hands-on experience with tools and technologies
SIEM platforms, Python for AI, ML algorithms, and security frameworks
Real-world projects and case studies to develop practical, deployable solutions
Why Choose This Program?
Industry-Relevant Curriculum
Designed by cybersecurity and AI experts to meet today’s tech demands
01
Hands-On Learning
Practical projects, labs, and simulations that ensure real-world application
02
Career-Boosting Opportunities
Certificate recognized in tech industries; potential pathways to roles like AI Security Analyst, Ethical Hacker, and Cyber Defense Specialist.
03
Expert Mentorship
Guidance from industry practitioners to accelerate learning and career growth
04
Flexible Learning
Structured for working professionals with interactive sessions and project-based assessments
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.
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.
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.
Core Modules
Foundations of Cybersecurity
Introduction to Artificial Intelligence
AI-Driven Security Solutions
Risk Management & Compliance
Hands-On Labs and Capstone Project
Who Is This Program For?
> Aspiring Cybersecurity Professionals aiming to enhance their skill set with AI capabilities
> IT Professionals & Developers looking to pivot into cybersecurity and AI-driven roles
> AI Enthusiasts seeking to apply machine learning in security-critical domains
> Business Leaders & Decision-Makers who want a strategic understanding of AI-driven cybersecurity
That’s right – Funding just got easier! We partner with India’s top banks to support your journey to success. And, our ATLAS Scholarship is there to enable access to world-class education and lifelong growth.
