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M.Tech. Computer Science & Engineering - ARTIFICIAL INTELLIGENCE
Program details
The UPES School of Computer Science offers a comprehensive M.Tech. program in Computer Science and Engineering with a specialization in Artificial Intelligence and Machine Learning. Spanning two years, the curriculum is meticulously crafted to align with the dynamic needs of the industry. Merging academic expertise and industry insights, the program empowers students to excel in the realm of AI and ML.
From the onset of each semester, students delve into real-world applications of AI and ML, facilitated by a rigorous foundation in probability and applied statistics. This dual approach equips learners to comprehend both the theoretical underpinnings and practical dimensions of the technologies, fostering a holistic understanding. The program's strength lies in its immersive learning experiences, including two projects and an industry internship. By engaging in these hands-on projects, students hone their application-oriented skills and solidify their grasp of technological fundamentals. Furthermore, the industry internship serves as a gateway to multiple pre-placement offers, underscoring the program's industry-relevance and career-enhancing potential.
The pedagogical methodology takes a unique twist by involving students in faculty research endeavors. This synergy not only enriches the educational journey but also provides opportunities to contribute to projects of national and international significance. This distinctive feature intertwines academia and real-world impact, fostering a holistic development of students. In conclusion, the M.Tech. program in AI and ML at UPES School of Computer Science strikes a balance between theoretical knowledge and practical application. With a forward-looking curriculum, hands-on projects, industry exposure, and research involvement, the program nurtures adept professionals prepared to navigate the ever-evolving landscape of Artificial Intelligence and Machine Learning.
Program Highlights
- Gain expertise in AI, Machine Learning, Neural Networks, and more, along with real-world applications in robotics, cognitive analytics, and natural language processing.
- Master programming languages including Python, Java, Scala, and C++, enhancing your coding skills for AI and ML development.
- The M.Tech. Computer Science & Engineering (Artificial Intelligence) program provides access state-of-the-art computer labs with high-speed internet, cloud computing tools, and top-tier software for practical learning. Specialized AIML labs offer hands-on experience with powerful hardware setups.
- Benefit from UPES's partnerships with international universities, allowing participation in exchange programs, study tours, and conferences, fostering a global perspective.
- Engage in real-world projects and internships with leading IT companies like IBM, Xebia, and AWS Academy through strong industry-academia partnerships.
- Meritorious students receive scholarships, while financial assistance and loan schemes ensure accessibility to quality education, regardless of socio-economic background.
Future Scope / Industry Trends
The M.Tech. Computer Science & Engineering (Artificial Intelligence) program at UPES School of Computer Science offers a promising future. With a projected 25% performance advantage by 2026 for enterprises using AI engineering practices, the demand for AI expertise is soaring. This century's groundbreaking inventions, like self-driven vehicles, robot assistance, and digital disease diagnostics, are products of AI's rapid progress. The program taps into this transformative wave, preparing professionals to lead AI research and development. AI & ML engineering is set to create numerous career opportunities, with up to 2.3 million prospects anticipated by 2020. The program aligns with industry demands, as Machine Learning developers, software technologists, and data scientists remain highly sought after. AIML specialists from this program engage in cutting-edge advancements, working on intricate challenges such as natural language understanding, image recognition, autonomous systems, and personalized recommendations, ultimately driving innovation and enhancing lives.
Career Opportunities
Upon graduating from the M.Tech. Computer Science & Engineering (Artificial Intelligence) program at UPES School of Computer Science, graduates are frequently recruited by leading companies. The program equips students with the sought-after skills in Artificial Intelligence and Machine Learning (AIML), positioning them favorably in a job market with high demand. Armed with a comprehensive understanding of molecular interactions through the application of physical principles, students can pursue roles such as Data Scientist, Machine Learning Engineer, Research Scientist, Business Intelligence Developer, AI Data Analyst, Big Data Engineer, Robotics Scientist, and AI Engineer. These diverse opportunities span industries and reflect the program's commitment to producing adept professionals capable of driving innovation and addressing complex challenges in the realm of AI and computer science.
Placements
The M.Tech. Computer Science & Engineering (Artificial Intelligence) program at UPES School of Computer Science has consistently demonstrated remarkable placements, reaffirming its commitment to producing highly skilled AI professionals. With a curriculum designed to foster in-depth understanding and practical proficiency in AI technologies, graduates are well-equipped to meet industry demands. UPES's strong industry connections facilitate collaborations, internships, and projects that align with real-world AI challenges. As a result, graduates showcase a versatile skill set, enabling them to seamlessly integrate into diverse sectors such as healthcare, finance, technology, and more. The dedicated placement cell ensures a seamless transition from academia to industry, organizing recruitment drives, mock interviews, and skill enhancement workshops. With a proven track record of placements in top-tier companies, the M.Tech. AI program at UPES empowers students to embark on successful and impactful AI careers.
Fee Structure
Click here for detailed Fee Structure.
Curriculum
Semester 1
Course | L | T | P | Credits |
---|---|---|---|---|
Design and Analysis of Algorithms | 3 | 0 | 1 | 4 |
Database Systems | 3 | 0 | 1 | 4 |
Distributed Systems | 3 | 0 | 1 | 4 |
Program Elective - I | 3 | 0 | 1 | 4 |
Program Elective - II | 3 | 0 | 1 | 4 |
Topics in Mathematical Sciences | 3 | 0 | 0 | 3 |
EDGE - Softskills | 1 | 0 | 0 | 0 |
Semester 2
Course | L | T | P | Credits |
---|---|---|---|---|
Advanced Algorithms | 3 | 0 | 1 | 4 |
Modelling and Simulation | 2 | 0 | 1 | 3 |
Research Methodology | 3 | 0 | 0 | 3 |
Applied DevOps | 3 | 0 | 1 | 4 |
Program Elective - III | 3 | 0 | 1 | 4 |
Program Elective - IV | 3 | 0 | 0 | 3 |
EDGE - Advanced Communication | 1 | 0 | 0 | 0 |
Semester 3
Course | L | T | P | Credits |
---|---|---|---|---|
Summer Internship | 0 | 0 | 1 | 1 |
Project Phase - 1 | 0 | 0 | 0 | 15 |
,
Semester 4
Course | L | T | P | Credits |
---|---|---|---|---|
Project Phase - 2 | 0 | 0 | 20 | 20 |
,
Electives for Artificial Intelligence
Course | L | T | P | Credits | Remarks | |
---|---|---|---|---|---|---|
PE - 1 | Applied Machine Learning | 3 | 0 | 1 | 4 | Mandatory |
PE - 2 | Deep Learning | 3 | 0 | 1 | 4 | Mandatory |
PE - 3 | Pattern Recognition | 3 | 0 | 1 | 4 | Mandatory |
PE - 4 | Natural Language Processing | 3 | 0 | 0 | 3 | Choose one |
PE - 4 | Generative AI | 3 | 0 | 0 | 3 | Choose one |
PE - 4 | Computer Vision | 3 | 0 | 0 | 3 | Choose one |
Eligibility
Interested students must meet the following minimum eligibility criteria for the M.Tech. program in Computer Science & Engineering (Artificial Intelligence):
- Minimum 60% marks at Higher and Senior Secondary level (X and XII).
- B. Tech/ BE (IT/(Hons.) Computer Science and Engineering), MCA, M.Sc. (Physics/Math’s/Statistics, with minimum 60% marks. Or Equivalent.
Selection Criteria
Selection for the M.Tech. in Computer Science & Engineering (Artificial Intelligence) program at UPES is determined by evaluating the performance of students in Personal Interview.
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