What if your smartphone predicts your next text, your car parks itself and doctors use algorithms to detect tumours invisible to the human eye? It is possible in a world powered by Artificial Intelligence (AI) and Machine Learning (ML), technologies that are reshaping industries at a breakneck pace. By 2030, AI could contribute up to $15.7 trillion to the global economy, whereas the Global Machine Learning Market size is expected to reach $408.4 billion by 2030, rising at a CAGR of 36.7%.
But you can keep up with this trend by pursuing a B.Tech AI and ML, a degree designed not just to keep pace with innovation but to lead it. As algorithms grow smarter and automation becomes ubiquitous, professionals who can design, train, and ethically deploy AI systems are no longer optional—they’re essential.
The B.Tech in Artificial Intelligence & Machine Learning (AI & ML) is a cutting-edge, four-year undergraduate programme designed to equip students with the expertise to pioneer next-generation technologies. As industries worldwide undergo rapid digital transformation, this degree bridges theoretical foundations with practicals, empowering graduates to engineer intelligent systems capable of autonomous learning, decision-making and problem-solving.
| Level of Programme | Undergraduate |
| Programme Duration | 4 Years |
| Eligibility Criteria | Applicants qualifying their 10+2 exam from a recognised Board and Science stream (Physics and Mathematics compulsory subjects) are eligible |
| Admission Process | Both the Entrance and Merit-based admission processes |
| Average Course Fee | INR 1,00,000-1.5 Lakhs |
| Average Starting Salary | Between 10 LPA and 15 LPA |
| Job Profiles | Data Analyst, Data Scientist, Data Engineer, Principal Data Scientist, Computer Vision Engineer, etc |
AI and ML is a career that requires a competent combination of good educational qualifications, strong technical know-how, and soft skills at a master’s level. The basic entry into this fast-moving domain is a degree in computer science, artificial intelligence, data science, or related areas, including a B.Tech in AI and ML.
To thrive in this field, students must be analytical, innovative and proficient in solving complex problems. Here’s a comprehensive look at the skills required:
| Skill | Description |
| 1. Programming Skills | Proficiency in Python, R, Java, or C++ is essential for developing AI/ML models. |
| 2. Mathematics and Statistics | Strong knowledge of linear algebra, probability, calculus, and statistics to understand ML algorithms. |
| 3. Data Analysis & Visualisation | Ability to clean, analyse, and visualise data to uncover patterns and insights. |
| 4. Machine Learning Algorithms | Familiarity with supervised, unsupervised, and reinforcement learning techniques. |
| 5. Deep Learning | Experience with tools like TensorFlow, Keras, and PyTorch for training neural networks. |
| 6. AI Frameworks & Libraries | Proficiency in Scikit-learn, OpenCV, NLTK, TensorFlow, and PyTorch enhances development speed and efficiency. |
| 7. Data Structures & Algorithms | Solid foundation in data structures and algorithm design to build efficient AI solutions. |
| 8. Big Data Technologies | Knowledge of Apache Spark and Hadoop for processing large datasets. |
| 9. Cloud Computing | Experience with AWS, Microsoft Azure, or Google Cloud for deploying scalable AI applications. |
| 10. Software Development Practices | Familiarity with software engineering, version control (Git), and API development for building production-ready systems. |
| Skill | Description |
| Problem-Solving Ability | Essential for solving real-world challenges using AI technologies. |
| Analytical Thinking | Helps in breaking down complex problems and drawing logical conclusions from data. |
| Communication Skills | Important for conveying technical ideas clearly to both technical and non-technical audiences. |
| Team Collaboration | Necessary for working effectively in interdisciplinary teams. |
| Adaptability & Curiosity | Willingness to learn, adapt, and stay updated with the latest AI/ML trends and technologies. |
A B.Tech AI and ML curriculum is structured to provide students with a strong foundation in computer science, mathematics and core AI principles. Here are some key subjects covered in the programme:
Practical Learning & Projects:
With AI taking centre stage in technological advancements, a B.Tech in AI and ML opens doors to diverse career paths across industries. Here are some of the top job roles with their scope:
With the increasing transition to data-driven decision-making and automation, B.Tech graduates specialising in AI and ML are in demand in India and around the globe. These professionals can pursue careers as Machine Learning Engineers, AI Architects, Data Scientists, Robotics Experts, and AI Research Engineers in companies like:
These companies actively seek AIML graduates for their ability to build intelligent systems, develop innovative solutions and lead cutting-edge research and development in AI-driven technologies.
The B.Tech in AI & ML syllabus covers core subjects like data structures, algorithms, computer vision, deep learning and neural networks. It includes programming languages like Python and R, AI ethics, cloud computing and big data analytics. Practical labs, projects and internships enhance hands-on learning and industry readiness. Here is an overview of the syllabus:
For students pursuing a B.Tech in Artificial Intelligence and Machine Learning, having the right set of books is essential to master both the theoretical foundations and practical aspects of the field. A well-rounded collection includes textbooks on mathematics, programming, data structures and software engineering. Here is a comprehensive look:
| Category | Book Title | Author(s) | Publisher / Edition |
| Mathematics & Logic | Discrete Mathematics and Its Applications with Combinatorics and Graph Theory | Kenneth H. Rosen | TMH, 7th Edition |
| Discrete Mathematics | Richard Johnsonbaugh | Pearson Education, 7th Edition | |
| Programming & Data Structures | Core Python Programming | Wesley J. Chun | Pearson, 2nd Edition |
| Fundamentals of Data Structures in C | E. Horowitz, S. Sahni, Susan Anderson Freed | Universities Press | |
| Advanced Programming in the UNIX Environment | W.R. Stevens | Pearson Education | |
| Computer Architecture | Computer System Architecture | M. Morris Mano | Pearson/PHI, 3rd Edition |
| Software Engineering | Software Engineering: A Practitioner’s Approach | Roger S. Pressman | McGraw-Hill, 6th Edition |
| Databases | Database System Concepts | Silberschatz, Korth | McGraw-Hill, 5th Edition |
Admission is typically based on national or university-specific entrance exams:
A B.Tech in AI and ML has opened doors for a dynamic and fulfilling future with escalating demand in other sectors. It spans various job profiles and serves as the foundation on which the growth of contemporary technology advances. Here’s a comprehensive look at the future scope:
The Apollo University stands among the top institutions committed to providing quality multidisciplinary education that prepares students to be career-ready. By integrating technology, management and healthcare, the university fosters transformative learning experiences, encouraging innovation, critical thinking and research-driven excellence.
B.Tech CSE–Artificial Intelligence and Machine Learning programme, offered under the School of Technology, is designed to provide students with cross-disciplinary knowledge and hands-on experience. Through real-world applications, students develop the ability to tackle complex challenges using cutting-edge AI and ML techniques.
At The Apollo University, education goes beyond textbooks—students gain practical exposure, leadership skills and problem-solving abilities through clubs, societies and interactive learning modules. The university nurtures future AI leaders by promoting a dynamic learning environment that encourages deep analysis and inquiry.
The question isn’t whether AI will reshape our world—it’s how. A B.Tech in AI & ML arms you to steer this change, whether you’re building ethical algorithms, pioneering smart cities, or decoding genomic data. With demand outstripping supply, this degree isn’t just an education—it’s a strategic advantage. Ready to lead the AI revolution? Explore The Apollo University’s B.Tech CSE in Artificial Intelligence and Machine Learning.
Yes, pursuing B.Tech in AI and ML is definitely worth it. Students pursuing BTech in AI and ML can get never-ending learning opportunities.
An AI and ML Engineer’s annual compensation is expected to be INR 9 Lakhs, with an average of INR 8.5 Lakhs depending on your job role and position.
There is no clear “better” option between CSE and AI; both provide promising career pathways, but CSE offers a more comprehensive foundation, while AI is more specialised and in demand. Your interests and professional objectives will determine the best option.
Some of the common ones include: JEE Main & JEE Advanced, conducted by NTA for admissions in NITs, IITs and other reputed colleges. BITSAT admission test is for BITS Pilani and its campuses.
Yes, you can definitely pursue a B.Tech in AI & ML after completing your 12th class. Many universities also offer AI-related courses, including B.Tech AI& Data Science. These programmes are designed to provide a strong foundation in AI concepts and technologies.
