You can apply online through the official website. Admission is based on academic merit or scores from recognized entrance exams.
About Programme
BTech CSE - Specialization in Data Science is a four-year undergraduate program offered by Apex University. This comprehensive program equips students with the knowledge and skills required to become successful data scientists. The program is designed to hone the students` technical, analytical, and problem-solving skills while also teaching them the basics of data storage, analysis, and machine learning. The program starts with a comprehensive introduction to the fundamentals of data science, including the basics of machine learning, statistics, software engineering, and data visualization. Subsequent courses explore advanced topics such as natural language processing, deep learning, and artificial intelligence. The program also provides students with the opportunity to learn practical applications of data science through a variety of hands-on projects. The BTech in Data Science program also allows students to develop their professional and communication skills. Through various lectures and seminars, students are taught how to effectively collaborate with teams, present data-driven solutions, and work in a cross-functional environment. Students also learn to use data-driven decision-making strategies to identify and solve complex problems. Throughout the program, students gain the skills and knowledge necessary to become successful data scientists. Graduates of the program are prepared to work in various industries, including finance, healthcare, government, and technology. With the proper training and experience, graduates can go on to pursue leadership roles in organizations and become experts in the field of data science.
Course Details
Eligibility Criteria
Passed 10+2 examination with Physics / Mathematics / Chemistry / Computer Science / Electronics / Information Technology / Biology / Informatics Practices / Biotechnology / Technical Vocational subject / Agriculture / Engineering Graphics / Business Studies / Entrepreneurship.(Any of the three)Obtained at least 50% marks for General(45% marks in case of candidates belonging to reserved category)in the above subjects taken together.
Fees Per Semester
65000/-
Duration / Schedule
4 Years (8 Semesters)
Seat Metrix
50% CUET and 50 % AUCET
SCHOLARSHIP AVAILABLE
Scholarship up-to 10 Lacs available for meritorious students
Check Eligibility
Programme Structure
| Semester 1 | |
|---|---|
| THEORY PAPER | PRACTICAL PAPER |
| - Engineering Mathematics-I | - Engineering Physics Lab |
| - Engineering Physics | - Basic Electronics and Electrical Engineering Lab |
| - Basic Electronics and Electrical Engineering | - Workshop Practice Lab |
| - English-I | - Basic Mechanical Engineering Lab |
| - Basic Mechanical Engineering | - English Language Lab |
| Semester 2 | |
|---|---|
| THEORY PAPER | PRACTICAL PAPER |
| - Engineering Mathematics-II | - Engineering Chemistry Lab |
| - Engineering Chemistry | - Programming with C for Problem Solving Lab |
| - Programming with C for Problem Solving | - Engineering Graphics and Design Lab |
| - Human Values | - Digital Electronics and Logic Design Lab |
| - Engineering Graphics and Design | - Internship Programme |
| - Digital Electronics and Logic Design | - Social Outreach, Discipline and Curriculum Activities |
| Semester 3 | |
|---|---|
| THEORY PAPER | PRACTICAL PAPER |
| - Discrete Mathematics | - Operating Systems Lab |
| - Computer Fundamentals and Organization | - Data Structures and Algorithms Lab |
| - Operating Systems | - Computer Networks Lab |
| - Data Structures and Algorithms | - Social Outreach, Discipline and Curriculum Activities |
| - Computer Networks | |
| - Critical Thinking | |
| Semester 4 | |
|---|---|
| THEORY PAPER | PRACTICAL PAPER |
| - Database Management Systems | - Database Management Systems Lab |
| - Introduction to Data Science | - Object Oriented Programming Python Lab |
| - Object Oriented Programming using Python | - Coding and Computational Thinking-I |
| - Inferential Statistics | - Internship Programme |
| - Communication Skills | - Social Outreach, Discipline and Curriculum Activities |
| - Open Elective-I | |
| - Principles of Management | |
| - Basics of Accounting | |
| Semester 5 | |
|---|---|
| THEORY PAPER | PRACTICAL PAPER |
| - Artificial Neural Networks | - Artificial Neural Networks Lab |
| - Data Analytics using SQL | - Data Analytics using SQL Lab |
| - Software Engineering | - Soft Skills and Aptitude-I |
| - Collaborative Team Work | - Coding and Computational Thinking -II |
| - Open Elective-II | - Mini Project |
| - Introduction to Entrepreneurship | - Social Outreach, Discipline and Curriculum Activities |
| - Necessary statistics | |
| Semester 6 | |
|---|---|
| THEORY PAPER | PRACTICAL PAPER |
| - NoSQL Databases | - Coding and Computational Thinking �III |
| - Big Data Analytics | - Placement Training |
| - Machine Learning | - Minor Project |
| - Multicultural Competence | - Social Outreach, Discipline and Curriculum Activities |
| - Open Elective- III | - NoSQL Databases Lab |
| - Digital Marketing | - Big Data Analytics Lab |
| - Human Resource Management | - Machine Learning Lab |
| - Soft Skills and Aptitude-II | |
| Semester 7 | |
|---|---|
| THEORY PAPER | PRACTICAL PAPER |
| - Data Visualization | - Data Visualization Lab |
| - Time Series Analysis | - Time Series Analysis Lab |
| - Departmental Elective-I | - Departmental Elective-I Lab |
| - Recommender Systems | - Recommender Systems Lab |
| - Advanced Machine Learning | - Advanced Machine Learning Lab |
| - Open Elective-IV | - Project Based Internship |
| - Principles of Banking | - Social Outreach, Discipline and Curriculum Activities |
| - Production and Operations Management | |
| Semester 8 | |
|---|---|
| THEORY PAPER | PRACTICAL PAPER |
| - Departmental Elective-II | - Departmental Elective-II Lab |
| - Natural Language Processing | - Natural Language Processing Lab |
| - Data warehouse and Business intelligence | - Data warehouse and Business intelligence Lab |
| - Open Elective-V | - Major Project |
| - Customer Relationship Management | - Social Outreach, Discipline and Curriculum Activities |
| - Financial Services | |
Programme Objectives
B.Tech in Data Science Program at Apex University
The B.Tech in Data Science program at Apex University is crafted to empower students with the knowledge and skills needed to excel in the data-driven world. Through a blend of theoretical foundations and hands-on experience, students will become proficient in data science techniques and applications.
Program Objectives:
- Data Mastery: Develop a thorough understanding of data analysis, statistical modeling, machine learning, and big data technologies.
- Practical Application: Provide extensive hands-on training through real-world projects, internships, and collaborative industry experiences.
- Innovative Solutions: Foster creativity and innovation in developing data-driven solutions to contemporary challenges.
- Analytical Skills: Enhance analytical thinking and problem-solving abilities to interpret and leverage complex data sets.
- Ethical Data Practices: Integrate ethical considerations and responsible data practices into the curriculum, ensuring graduates make positive impacts with data.
- Career Preparedness: Prepare students for diverse roles in data science, analytics, machine learning, and related fields, equipping them with industry-relevant skills.
- Professional Development: Cultivate essential professional skills, including teamwork, communication, and project management, for successful careers in data science.
Course USPs
- Comprehensive Curriculum: Covers foundational and advanced topics in data science, including data analysis, statistical modeling, machine learning, data visualization, and big data technologies.
- Practical Experience: Emphasis on hands-on projects, internships, and lab work, allowing students to apply theoretical knowledge to real-world data challenges.
- Advanced Tools and Technologies: Training on industry-standard tools and platforms such as Python, R, SQL, Hadoop, and Spark, ensuring students are well-versed in current data science practices.
- Industry Collaboration: Partnerships with leading companies for guest lectures, collaborative projects, and internships, providing students with industry exposure and networking opportunities.
- Expert Faculty: Guidance from experienced professors and industry practitioners with deep knowledge in data science, offering mentorship and support.
- Interdisciplinary Approach: Integration of data science with other fields such as artificial intelligence, machine learning, and business analytics, broadening students' skill sets and career prospects.
- Career Readiness: Preparation for diverse roles such as data analysts, data scientists, machine learning engineers, and business intelligence analysts, focusing on developing critical thinking and problem-solving skills.
- Global Opportunities: Exposure to international collaborations, conferences, and exchange programs, enhancing students' global perspectives and career opportunities.
- State-of-the-Art Facilities: Access to modern labs, computing resources, and data analytics tools, providing an optimal learning environment for mastering data science.
Career Opportunities
Big Data Developer:
Works on large-scale data processing frameworks, develops analytical applications, and optimizes data flow for businesses handling massive datasets.
Business Intelligence Analyst:
Analyzes market trends, builds dashboards, and transforms raw data into actionable business insights using data visualization techniques and reporting tools.
Data Engineer:
Designs and maintains scalable data pipelines, optimizes data storage, and ensures data integrity for efficient real-time analytics and processing.
Data Analyst:
Interprets complex data sets, creates visual reports, identifies trends, and provides data-driven insights for strategic business decision-making and operational improvements.
Frequently Asked Questions
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1. How can I apply for the program?
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2. Are there scholarships available for this program?Yes, scholarships are offered based on academic performance, entrance exam results, and financial need.
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3. How can I apply for a scholarship?You can apply for scholarships during the admission process. Ensure that you provide all required documents, including entrance test scores, academic records, and any other necessary certifications.
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4. Is there a management quota or direct admission available?Apex University primarily admits students through AUCET and CUET. However, for details about specific admission pathways, you may contact the admissions office.
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5. What facilities are available for students at Apex University?Apex University provides state-of-the-art labs, a fully equipped library, modern classrooms, sports facilities, and hostel facility.
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Is there an opportunity for research in this field?Yes, the program encourages research in data-driven decision-making and machine learning algorithms.
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What industries require Data Science professionals?Data Scientists are needed in IT, healthcare, banking, retail, and entertainment sectors.
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Are projects based on real-world data included in the curriculum?Yes, students work on projects in domains like healthcare, finance, and e-commerce.
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Which tools and technologies are taught for Data Science?Tools like Python, R, Tableau, Hadoop, and TensorFlow are covered.
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What is the primary focus of a Data Science program?The focus is on data analysis, machine learning, big data technologies, and predictive modeling.
Placement Highlights
38LPA
Highest Package
10LPA
Avg. Package
14k+
Total Placements
700+
Placement Drives
Our Top Recruiters
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