B.Tech Computer Science and Engineering- Big Data
Program details
The B.Tech. Computer Science & Engineering (Big Data) program at UPES School of Computer Science is designed to equip students with a comprehensive understanding of big data concepts, technologies, and applications. The specialization focuses on building a strong foundation in big data infrastructure and management. Through this course, students will develop the skills needed to set up, administer, and utilize scalable data storage and processing systems effectively. The curriculum covers a range of essential topics, including distributed computing frameworks such as Hadoop and Spark, data storage systems like HDFS and NoSQL databases, and data processing tools like Hive and Pig. Moreover, students will gain insights into cloud-based platforms and services tailored for big data solutions. The program takes an immersive approach by providing hands-on training on the Cloudera platform during summer sessions, allowing students to gain practical experience with industry-standard tools.
To enrich their learning journey, students will have the unique opportunity to interact with industry experts and professionals from Xebia through webinars and interactive sessions. These interactions will provide real-world insights and current trends in the big data landscape, fostering a holistic understanding of the field. Additionally, mentors will be readily available to guide students throughout their capstone projects, encouraging them to delve into research papers, industry publications, and even attend conferences and workshops to stay updated on the latest advancements in big data technologies and applications.
In conclusion, the B.Tech. Computer Science & Engineering (Big Data) program offered by UPES School of Computer Science offers a comprehensive educational experience. It equips students with the necessary skills to excel in the world of big data by providing a strong foundation in key technologies, hands-on training, industry exposure, and guidance from mentors. This program empowers students to become adept in harnessing the potential of big data for solving complex real-world challenges and driving innovation across various industries.
Program Highlights
- The B.Tech. Computer Science & Engineering (Big Data) program extensively covers essential Big Data tools like Hadoop Ecosystem, Spark, Kafka, and more, alongside programming languages such as Python, Java, Scala, and C++.
- The UPES School of Computer Science boasts advanced computer labs with high-end systems and high-speed internet, complemented by a well-equipped library for research and study.
- Dedicated Big Data labs offer immersive hands-on experience with high-end systems, enabling students to explore distributed computing frameworks like Hadoop and Spark.
- Through partnerships with international universities, students can engage in exchange programs, study tours, and conferences to broaden their horizons.
- Strong ties with industry leaders like IBM, Xebia, and AWS Academy provide opportunities for real-world projects, internships, hackathons, and coding competitions.
- Meritorious students can benefit from scholarships based on academic performance and other achievements, while financial assistance and loan schemes are available for deserving candidates.
Future Scope / Industry Trends
The future scope of the B.Tech. Computer Science & Engineering (Big Data) program by UPES School of Computer Science is promising and aligned with emerging trends. As technology advances, automation powered by AI algorithms will enhance data processing, analysis, and decision-making, facilitating quicker and more precise insights from big data. Real-time processing of streaming data will be a priority, enabling instant insights for proactive decision-making. The rise of IoT devices will necessitate edge computing, ensuring real-time analysis at the network edge, reducing latency and bandwidth needs. Hybrid and multi-cloud strategies will optimize big data storage and processing, while privacy-preserving techniques will address data security concerns. DataOps methodologies will streamline integration and collaboration among stakeholders. Graph databases and knowledge graphs will gain traction for interconnected data storage and context enhancement. Ethical considerations and data governance will be emphasized, and AI-driven tools will automate data preparation. Federated learning will enable privacy-preserving model training. The program equips students to excel in this dynamic landscape by imparting knowledge and skills aligned with these trends.
Career Opportunities
Completing a B.Tech. in Computer Science & Engineering with a specialization in Big Data from UPES School of Computer Science opens up a plethora of promising career opportunities in the dynamic world of technology. With an average annual package of 8.70 LPA and a remarkable highest package of 26.41 LPA, graduates can embark on fulfilling journeys in various sectors. They can choose to become data engineers, leveraging their skills to design, construct, install, and maintain large-scale data processing systems. Alternatively, they can opt for roles as data analysts, extracting valuable insights from complex datasets to drive informed business decisions. The field of machine learning engineering also beckons, allowing graduates to craft intelligent algorithms and models that power AI-driven solutions. Moreover, opportunities in cloud computing, cybersecurity, and software development are equally abundant. Whether driving innovation as data scientists, shaping user experiences as UX/UI designers, or steering tech ventures as entrepreneurs, UPES graduates are well-equipped to excel, armed with both theoretical knowledge and practical skills. The program's impressive placement statistics reflect the abundant prospects awaiting those who embark on this educational journey.
Placements
The B.Tech. Computer Science & Engineering (Big Data) program at UPES School of Computer Science consistently demonstrates an exceptional record in placements, showcasing the institution's commitment to producing highly skilled professionals. The program's curriculum, thoughtfully designed to align with industry demands, equips students with a deep understanding of Big Data technologies and their applications. This proficiency is evident in the remarkable placements achieved by graduates, who find themselves in enviable positions across diverse sectors. Renowned companies actively recruit UPES students, recognizing their adeptness in areas like data analytics, machine learning, and data engineering. This program's success in securing placements can be attributed to the blend of theoretical knowledge and hands-on experience it imparts, fostering well-rounded graduates who are poised to make significant contributions in the dynamic realm of Big Data.
Fee Structure
Click here for detailed Fee Structure.
Curriculum
Semester 1
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Linux Lab | 0 | 0 | 4 | 2 |
| Programming in C | 0 | 0 | 3 | 3 |
| Programming in C Lab | 0 | 0 | 4 | 2 |
| Problem Solving | 2 | 0 | 0 | 2 |
| Living Conversation | 2 | 0 | 0 | 2 |
| Advanced Engineering Mathematics – I | 3 | 1 | 0 | 4 |
| Environmental Sustainability and Climate Change - I | 2 | 0 | 0 | 2 |
| Physics for Computer Engineers | 4 | 0 | 0 | 4 |
| Physics for Computer Engineers Lab | 0 | 0 | 2 | 1 |
| TOTAL | 22 |
Semester 2
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Computer organization and Architecture | 3 | 0 | 0 | 3 |
| Data Structures and algorithms | 4 | 0 | 0 | 4 |
| Data Structures and algorithms Lab | 0 | 0 | 2 | 1 |
| Python programming | 2 | 0 | 0 | 2 |
| Python programming Lab | 0 | 0 | 4 | 2 |
| Digital Electronics | 3 | 0 | 0 | 3 |
| Critical Thinking and Writing | 2 | 0 | 0 | 2 |
| Advanced Engineering Mathematics – II | 3 | 1 | 0 | 4 |
| Environmental Sustainability and Climate Change - II | 2 | 0 | 0 | 2 |
| TOTAL | 23 |
Semester 3
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Database Management Systems | 3 | 0 | 0 | 3 |
| Database Management Systems Lab | 0 | 0 | 4 | 2 |
| Discrete Mathematical Structures | 3 | 0 | 0 | 3 |
| Object Oriented Programming | 3 | 0 | 0 | 3 |
| Object Oriented Programming Lab | 0 | 0 | 2 | 1 |
| Operating Systems | 3 | 0 | 0 | 3 |
| Software Engineering | 3 | 0 | 0 | 3 |
| Exploratory-1 | 0 | 0 | 0 | 3 |
| Design Thinking | 0 | 0 | 0 | 2 |
| TOTAL | 23 |
Semester 4
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Artificial Intelligence and Machine Learning | 2 | 0 | 0 | 2 |
| Artificial Intelligence and Machine Learning Lab | 0 | 0 | 2 | 1 |
| Data communication and Networks | 3 | 0 | 0 | 3 |
| Data communication and Networks Lab | 0 | 0 | 2 | 1 |
| Design and Analysis of Algorithms | 3 | 0 | 0 | 3 |
| Design and Analysis of Algorithms Lab | 0 | 0 | 2 | 1 |
| Exploratory-2 | 3 | 0 | 0 | 3 |
| Linear Algebra | 3 | 0 | 0 | 3 |
| PE-1 | 4 | 0 | 0 | 4 |
| PE-1 Lab | 0 | 0 | 2 | 1 |
| TOTAL | 22 |
Semester 5
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Cryptography and Network Security | 3 | 0 | 0 | 3 |
| Formal Languages and Automata Theory | 3 | 0 | 0 | 3 |
| Object Oriented Analysis and Design | 3 | 0 | 0 | 3 |
| Exploratory-3 | 3 | 0 | 0 | 3 |
| Start your Startup | 2 | 0 | 0 | 2 |
| Research Methodology in CS | 3 | 0 | 0 | 3 |
| Probability, Entropy, and MC Simulation | 3 | 0 | 0 | 3 |
| PE-2 | 4 | 0 | 0 | 4 |
| PE-2 Lab | 0 | 0 | 2 | 1 |
| TOTAL | 25 |
Semester 6
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Exploratory-4 | 3 | 0 | 0 | 3 |
| Leadership and Teamwork | 2 | 0 | 0 | 2 |
| Compiler Design | 3 | 0 | 0 | 3 |
| Statistics and Data Analysis | 3 | 0 | 0 | 3 |
| PE-3 | 4 | 0 | 0 | 4 |
| PE-3 Lab | 0 | 0 | 2 | 1 |
| Minor Project | 0 | 0 | 5 | 5 |
| TOTAL | 21 |
Semester 7
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Exploratory-5 | 3 | 0 | 0 | 3 |
| PE-4 | 4 | 0 | 0 | 4 |
| PE-4 Lab | 0 | 0 | 2 | 1 |
| PE-5 | 3 | 0 | 0 | 3 |
| PE-5 Lab | 0 | 0 | 2 | 1 |
| Capstone Project - Phase-1 | 0 | 0 | 5 | 5 |
| Summer Internship | 0 | 0 | 0 | 1 |
| TOTAL | 18 |
Semester 8
| Course | L | T | P | Credit |
|---|---|---|---|---|
| IT Ethical Practices | 3 | 0 | 0 | 3 |
| Capstone Project - Phase-2 | 0 | 0 | 5 | 5 |
| TOTAL | 8 |
Program Elective 24 Credits
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Fundamentals of Data Science | 4 | 0 | 0 | 4 |
| Fundamentals of Data Science Lab | 0 | 0 | 2 | 1 |
| Data Visualization and Interpretation | 4 | 0 | 0 | 4 |
| Data Visualization and Interpretation Lab | 0 | 0 | 2 | 1 |
| Machine Learning and Deep Learning | 4 | 0 | 0 | 4 |
| Machine Learning and Deep Learning Lab | 0 | 0 | 2 | 1 |
| Computational Linguistic & Natural Language Processing | 4 | 0 | 0 | 4 |
| Computational Linguistic & Natural Language Processing Lab | 0 | 0 | 2 | 1 |
| Generative Artificial Intelligence | 3 | 0 | 0 | 3 |
| Generative Artificial Intelligence Lab | 0 | 0 | 2 | 1 |
| TOTAL | 24 |
Eligibility
Interested students must meet the following minimum eligibility criteria for the B.Tech. Computer Science & Engineering (Big Data) program: Minimum 50% Marks in Class X and XII. Along with 50 % in PCM (Physics/Chemistry and Mathematics) in Class XII.
Selection Criteria
The selection criteria for individuals who wish to pursue B.Tech. in Computer Science & Engineering (Big Data) at UPES School of Computer Science relies on the individual's performance in UPESEAT / JEE Mains / Board Merit / SAT/ CUET.
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Frequently Asked Questions
Yes, Big Data remains a strong career option, particularly as organisations increasingly rely on AI and data-driven technologies. AI systems need large volumes of clean, structured, and reliable data to learn and perform effectively. Big Data professionals help build the systems and infrastructure used to collect, process, store, and manage this data. As AI adoption continues to grow, the demand for professionals who can manage the data powering these systems is likely to remain strong.
Big Data, Data Science, and Artificial Intelligence are technologies that serve different purposes but work in the same field. The Big Data refers to the massive raw stored information, Data Science analyses the massive data and identifies patterns and trends, and Artificial Intelligence builds smart systems from based on the analysed data.
Yes, a B.Tech in Big Data at UPES includes areas such as Cloud Computing and Data Engineering. Cloud Computing helps you learn how to store, process, and manage large datasets using scalable cloud infrastructure, while Data Engineering focuses on building data pipelines and systems for collecting, processing, and organising data.
Some of the key skills that UPES’s B.Tech Big Data specialization offer include core programming, data storage systems, data processing tools, and machine learning. Furthermore, the program also emphasizes on practical skill-based learning through internships and project works. The course also offers industry-ready skills through certificate programs such as advanced Applied AI & Data Engineering certification.
The most commonly used programming languages in Big Data include Python, Java, Scala, and SQL. These languages are widely used with popular Big Data processing technologies such as Apache Spark and Apache Hadoop. Learning these tools can help you work with large datasets, build data pipelines, and process information efficiently at scale. UPES Dehradun offers programming languages and advanced technologies into the B.Tech CSE Big Data program to prepare students for future ready careers in diverse industries.
During a B.Tech in Big Data at UPES Dehradun, you can work on real-world projects that help you apply data processing and analytics concepts to practical problems. Examples include real-time social media sentiment analysis, predictive maintenance for factories, healthcare data management systems, smart traffic-flow optimisation, and large-scale e-commerce recommendation engines. These projects can give you hands-on experience in processing and analysing large volumes of data.
B.Tech Big Data graduates can pursue promising career opportunities in diverse industries including technology, banking and finance, e-commerce, healthcare, telecommunications, and government sectors. UPES offers students placement support through top recruiters and placement drivers to help students get the best career opportunities.
A B.Tech in Computer Science and Engineering (CSE) - Big Data can prepare you for a range of data-focused technology careers. Popular roles include Big Data Engineer, Data Scientist, Data Analyst, Machine Learning Engineer, and Business Intelligence Developer. Graduates can explore opportunities across industries such as technology, finance, e-commerce, and healthcare, where organisations rely on professionals to manage, process, and analyse large volumes of data.
Yes, a B.Tech in Big Data program at UPES provides a strong foundation for careers in Artificial Intelligence (AI) and Machine Learning (ML). Modern AI and ML systems depend on large volumes of data for training, testing, and improving models. By learning how to collect, process, manage, and analyse large datasets, you can develop skills that complement AI and ML technologies and prepare for data-driven technology careers.
Yes, industry internships are essential for skill development and career development for students pursuing B.Tech Big Data. UPES Dehradun has incorporated mandatory internships into the core curriculum of the BTech CSE Big Data to allow students future-ready skills and prepare them for dynamic roles in diverse industries.
A Big Data degree provides a strong theoretical foundation, but industry-recognized certifications validate hands-on tool mastery. Some of the high-valued certification programs include AWS Certified Data Engineer-Associate, Google Cloud Professional Data Engineer, SAS Certified Big Data Professional. Additionally, UPES also integrates industry-ready advanced certification in Applied AI & Data Engineering to help with skill development among students.
A B.Tech in Computer Science and Engineering with a specialisation in Big Data can be a good fit if you enjoy mathematics, spotting patterns in large datasets, and solving complex problems. The program is particularly suited to students who want to learn how to build scalable systems that can collect, process, and analyse massive amounts of data for businesses, research, and other applications.
A Data Engineer builds and manages data pipelines, databases, and data warehouses to make information accessible for analysis and business use. A Big Data Engineer specialises in handling massive, complex, or unstructured datasets using distributed systems and specialised frameworks. In simple terms, Data Engineers work across general data infrastructure, while Big Data Engineers focus on building systems that can process data at very large scale.
Amazon Web Services, Google Cloud Platform, and Microsoft Azure are some of the key cloud platforms used in Big Data. These platforms have been incorporated into the UPES’s B.Tech Big Data program to offer students a comprehensive skill-based education.
Yes, B.Tech Big Data engineering program requires students to have a strong mathematics foundation. As per the B.Tech Big Data eligibility criteria, applicants are required to have a minimum 50% Marks in Class X and XII, along with a minimum of 50 % in PCM in Class XII.
Yes, UPES B.Tech CSE Big Data curriculum includes advanced certification in Applied AI & Data Engineering to offer skill-based learning opportunities to the students.
