Jain University Online
Data Analytics
Jain University Online
₹1.6L – ₹1.6L
Total Fees
3 Years
Duration
ONLINE
Mode
★ 4.0
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About This Program at Jain University Online
Course Curriculum
| Semester 1 | Semester 2 | Semester 3 | Semester 4 | Semester 5 | Semester 6 |
|---|---|---|---|---|---|
| Fundamentals of Computer Applications – Introduction to computer systems, software, hardware, and operating environments. | Data Structures and Algorithms – Arrays, stacks, queues, trees, and graphs, essential for problem-solving in computing. | Python Programming for Data Science – Python fundamentals, libraries (NumPy, Pandas), and scripting for data analysis. | Machine Learning Fundamentals – Supervised and unsupervised learning, classification, regression, clustering, and model evaluation. | Deep Learning and AI Applications – Neural networks, deep learning architectures, and practical AI implementations. | Capstone Data Science Project – Comprehensive project involving end-to-end data collection, processing, modeling, and visualization. |
| Programming in C – Basics of programming logic, problem-solving, and structured programming. | Object-Oriented Programming with C++/Java – OOP concepts such as inheritance, polymorphism, encapsulation, and abstraction. | Statistics and Probability for Analytics – Descriptive statistics, probability distributions, hypothesis testing, and regression analysis. | Big Data Technologies – Introduction to Hadoop, Spark, and handling large datasets for analysis. | Advanced Data Visualization and Reporting – Interactive dashboards and advanced reporting using Tableau, Power BI, or similar tools. | Cloud Analytics and IoT Data Management – Handling and analyzing data from cloud platforms and IoT devices. |
| Mathematics for Computing – Fundamentals of discrete mathematics, statistics, and probability for computing applications. | Database Management Systems (DBMS) – SQL programming, relational database design, and data manipulation. | Computer Networks and Security Basics – Network fundamentals, data transmission, and basic cybersecurity principles. | Business Intelligence and Decision Making – Tools and techniques to generate actionable insights and support strategic decisions. | Predictive Analytics and Forecasting – Using statistical and machine learning techniques to predict trends and outcomes. | Professional Development & Career Skills – Communication, teamwork, problem-solving, and career readiness workshops. |
| Communication Skills – Professional communication, technical writing, and presentation skills. | Environmental Studies – Understanding technology’s role in environmental sustainability and ethics. | Data Visualization – Techniques to represent data visually using charts, graphs, and dashboards. | Data Analytics Project / Lab – Hands-on application of analytics techniques to solve real-world problems. | Elective / Minor Project – Opportunity to apply knowledge in a domain-specific project or research study. | Cyber Ethics and Data Governance – Understanding ethical considerations, data privacy laws, and regulatory compliance in data handling. |
Learning Outcomes
What you will achieve after completing this program
Strong Computing and Programming Foundations: Students will develop a solid understanding of programming languages, algorithms, and data structures. These skills provide the backbone for advanced analytics tasks and enable students to write efficient code, manage data effectively, and implement data-driven solutions in real-world scenarios.
Proficiency in Data Analysis and Statistical Methods: Graduates will gain expertise in statistical modeling, probability, and data analysis techniques. They will be capable of interpreting complex datasets, identifying trends, and applying statistical reasoning to support decision-making in business and technology contexts.
Hands-On Skills in Data Science Tools and Technologies: Students will acquire practical experience with industry-standard tools and platforms such as Python, R, SQL, Tableau, Power BI, Hadoop, and Spark. This equips them to handle large-scale data processing, visualization, and predictive modeling, preparing them for real-world analytics challenges.
Expertise in Machine Learning and AI Applications: Graduates will learn to design, implement, and evaluate machine learning models, including supervised, unsupervised, and deep learning techniques. They will be able to develop AI-driven solutions for predictive analytics, recommendation systems, and other data-intensive applications.
Eligibility Criteria
Who Can Apply
Candidates must have completed 10+2 / Higher Secondary / PUC or equivalent examination from a recognized board.
A minimum of 45–50% aggregate marks in the qualifying examination, as per university norms.
Students from any stream (Science, Commerce, or Arts) are eligible to apply; however, a background in Mathematics or Computer Science is an advantage.
Required Documents
10th & 12th Marksheets
Graduation Certificate
Government ID Proof
Passport Size Photo
Finance Your Education
Total Program Fee
₹1.6L
≈ ₹28K per semester
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Scholarship
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Fee Structure
| Total Program Fee | ₹1.6L – ₹1.6L |
| Semester Fee | ₹28K |
| Duration | 3 Years |
| Mode | ONLINE |
| Exam Fee | Included |
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Data Analytics
Jain University Online