Inaugural Batch
Specialized Program in Artificial Intelligence and Machine Learning
with Autonomous Vehicle Technology
Qualifier Test Date
July 19, 2026
Program Duration
6 Months
Time Commitment
8-10 Hours/week
Eligibility
12th pass and above
Learning Mode
Online
3.3K+ students have already registered
Official Implementation Partner:
Masai School
Qualifier Test Date
July 19, 2026
Program Duration
6 Months
Time Commitment
8-10 Hours/week
Eligibility
12th pass and above
Learning Mode
Online
Why choose this course?
Gain the skills to design and manage AI-powered autonomous cars that shape tomorrow’s market.
Earn certification from TiHAN, IIT Hyderabad’s premier research hub for autonomous vehicle technology.
Learn from IIT faculty, industry experts, and TiHAN scientists, bringing real-world insights to your learning journey.
Gain in-depth knowledge with real-world applications across defense, agriculture and surveillance
Students with a CGPA of 9 or above will get direct interview opportunities at TiHAN, IIT Hyderabad
Join a 2-day on-campus experience at TiHAN IIT Hyderabad, exploring labs and engaging with experts.
Receive resume reviews, career coaching, and placement opportunities to land your dream role. (Eligibility: 7+ CGPA and 65% attendance; Fulfilled by Masai)
Certification by TiHAN – IIT Hyderabad
Earn certification from TiHAN, IIT Hyderabad’s premier research hub for autonomous vehicle technology.
Expert Faculty & Industry Insights
Learn from IIT faculty, industry experts, and TiHAN scientists, bringing real-world insights to your learning journey.
Complete 15-20 hours of specialized learning in Autonomous Vehicle Technology
Gain in-depth knowledge with real-world applications across defense, agriculture and surveillance
Assured Interview at TiHAN – IIT Hyderabad (Internship)
Students with a CGPA of 9 or above will get direct interview opportunities at TiHAN, IIT Hyderabad
Campus Immersion at TiHAN, IIT Hyderabad
Join a 2-day on-campus experience at TiHAN IIT Hyderabad, exploring labs and engaging with experts.
Placement Opportunity
Receive resume reviews, career coaching, and placement opportunities to land your dream role. (Eligibility: 7+ CGPA and 65% attendance; Fulfilled by Masai)
Certificate Eligibility Criteria: Minimum 65% overall attendance and minimum CGPA of 4.0.
Career Outcomes
Automotive Artificial Intelligence Software Engineer
₹21.3 LPA - ₹22.7 LPA
Develop AI systems for self-driving vehicles, drones, robotics, smart transportation, and autonomous navigation platforms.
Source: GlassdoorDeep Learning Engineer
₹6 LPA - ₹15.2 LPA
Build neural networks and advanced AI systems for NLP, vision AI, robotics, and generative AI applications.
Source: GlassdoorAI Engineer
₹15.2 LPA - ₹16.7 LPA
Create and deploy AI-powered solutions that automate tasks, improve decision-making, and solve real-world business problems.
Source: Ambition BoxComputer Vision Engineer
₹11.3 LPA - ₹12.9 LPA
Work on image recognition, object detection, autonomous navigation, surveillance, and smart mobility systems using OpenCV and deep learning.
Source: Ambition BoxAutonomous Vehicle & Smart Mobility market in India is growing at nearly 25% CAGR
Robotics & Autonomous Systems roles now pay up to ₹20 LPA+ for mid-level engineers
50,000+ AI/ML job openings are already active in India - but only ~15,000 candidates are considered industry-ready.
1 Million AI professionals will be needed in India by 2026
Meet our Instructor Team
What will you learn?
In the Artificial Intelligence and Machine Learning with Autonomous Vehicle Technology program from TiHAN - IIT Hyderabad, you will build a strong foundation in data science, explore core machine learning techniques, and understand ethical AI practices. Specialize in autonomous systems, focusing on perception, navigation, and real-time decision-making. Apply your learning through hands-on projects, developing intelligent solutions for real-world mobility challenges.
Toolkit
Course Details
Duration
6 Months
Course Mode
Online
Certification
from TiHAN IIT Hyderabad
- • Build confidence in core Python fundamentals such as variables, data types,conditionals, loops, functions, and file handling
- • Understand structured data, descriptive statistics, probability, and foundational data science concepts
- • Work with NumPy, Pandas, and visualization tools for data handling and interpretation
- • Develop practical data literacy through handling and exploring simple datasets
- • Build the programming and data foundations required for later AIML modules
- • Understand the basics of supervised and unsupervised learning
- • Apply foundational predictive models such as Linear Regression, Logistic Regression, Decision Trees, and Random Forests
- • Work with preprocessing, feature preparation, and model-ready datasets
- • Use evaluation metrics and model comparison methods to assess performance
- • Build confidence in using machine learning methods for practical prediction tasks
- • Understand the intuition behind neural networks and how they differ from classical machine learning models
- • Build familiarity with deep learning concepts and their role in perception-oriented problems
- • Recognize the role of image data and computer vision in intelligent systems
- • Work with perception-related workflows and visual interpretation tasks
- • Connect deep learning and perception concepts to autonomous systems applications
- • Understand how to structure machine learning projects from problem definition to model selection and improvement
- • Recognize the impact of data quality, class imbalance, leakage, and feature preparation on model performance
- • Interpret overfitting, underfitting, generalization, and model error through practical examples
- • Build familiarity with model tuning, experiment tracking, and comparison of alternative approaches
- • Understand deployment basics, inference workflows, model monitoring, and reliability in real-world AIML systems
- • Understand the key concepts behind LLMs, Generative AI, and AI agents
- • Recognize how modern AI systems differ from classical machine learning workflows
- • Identify practical use cases of GenAI and agent-based systems across industries
- • Understand how language-based AI, perception, and decision-making connect in intelligent systems
- • Relate emerging AI applications to autonomous systems and intelligent mobility use cases
- • Capstone brief: Learners will complete an applied AIML project that demonstrates their ability to work with data, apply machine learning or perception-oriented logic, and interpret an intelligent systems or autonomous vehicles use case in a structured way
- • Define a practical problem and identify relevant data or system inputs
- • Apply appropriate AIML methods using the tools and concepts learned in the program
- • Communicate outputs, limitations, and possible improvements clearly
- • Integrate an autonomous systems or intelligent mobility lens into the project framing where appropriate
Projects
Product-Image Classifier (CNN)
Flipkart’s catalog team wants to auto-categorise product images into Apparel, Electronics, and Home. You train a small CNN on a public Indian e-commerce image dataset using free Colab GPU, push validation accuracy past 85%, and produce a confusion-matrix breakdown that names exactly which category pairs the model still fumbles — and why.
DECISION OUTPUT
Trained classifier with documented confusion patterns the catalog team can route to manual review.
Customer-Churn Predictor & API
Build a churn-prediction model for a D2C customer dataset. Engineer RFM features (recency, frequency, monetary), train a gradient-boosting classifier, deploy as a FastAPI endpoint, and write the model card — including the ethical considerations around retention targeting that any real product team will probe in your interview.
DECISION OUTPUT
A deployable churn predictor with a documented model card you can defend to a hiring panel.
Note: The project deliverables or case studies for your batch may differ, as per the decision of the Institute or Course Faculty
Campus Immersion at TiHAN, IIT Hyderabad
Experience a transformative two-day, on-campus immersion at TiHAN IIT Hyderabad—where learning meets real-world application.
Key Highlights
Hands-on Simulations
Apply AI and autonomous vehicle concepts in practical project scenarios
Leadership in Action
Build strategic project management skills for real-world impact
Collaborative Learning
Solve challenges with a diverse, high-caliber peer group
Expert Interaction
Engage directly with expert mentors and programme leaders
Beyond Learning
Expand Your Network
Connect with professionals across industries
Gain New Perspectives
Broaden your approach to AI and project leadership
Outcome
Practical Confidence
Turn knowledge into real-world capability
Career-Ready Skills
Return with enhanced expertise and a strong professional network