Computer Engineering (Data Science)

About the Specialization

The Data Science specialization under the B.Tech in Computer Engineering at J.C. Bose University of Science and Technology, YMCA, equips students with in-demand skills in data analytics, machine learning, artificial intelligence, and big data technologies.

This program blends core computer science principles with data-driven decision making to address real-world problems through predictive models, deep learning, and business intelligence.

What You Will Learn

• Data Analysis using Python, R, and SQL
• Statistics, Linear Algebra, and Probability for Data Science
• Machine Learning & Deep Learning (TensorFlow, PyTorch)
• Big Data Tools: Hadoop, Spark, Hive
• Data Visualization using Tableau, Power BI, Matplotlib, Seaborn
• Natural Language Processing and Computer Vision
• Cloud Data Platforms: AWS, GCP, Azure
• Data Ethics, Privacy, and Governance

Laboratories and Tools

• Data Science and Analytics Lab with GPU support
• JupyterHub, RStudio, Anaconda, VS Code environments
• Cloud-integrated platforms (AWS Educate, Google Colab)
• Real-time dashboards and visualization labs
• IoT-enabled datasets and sensor integration for projects

Industry Collaboration

• MoUs with Google Cloud, TCS iON, and IBM Data Science Academy
• Live projects with industry mentors
• Hackathons and datathons at national/international levels
• Workshops and bootcamps on AI, ML, and Data Engineering

Career Opportunities

• Data Scientist / Data Analyst / Data Engineer
• Machine Learning Engineer / AI Researcher
• BI Analyst / Data Visualization Expert
• Cloud Data Architect / Database Administrator
• Quantitative Analyst / Product Analyst
• Research in Data Science or pursue M.S./Ph.D. programs

Student Highlights

• Top 1% performers in Kaggle competitions
• Internships at Adobe, Fractal Analytics, ZS Associates
• GSoC selections and international research collaborations
• Winning teams at Smart India Hackathon (ML track)

Admission and Eligibility

• Admission through JEE Main counseling via HSTES
• Strong mathematics background and interest in analytics
• 12th PCM with 75% aggregate (as per AICTE norms)
• Prior exposure to Python or statistics recommended