You can apply online through the official website. Admission is based on academic merit or scores from recognized entrance exams.
About Programme
The B.Tech in Data Science lateral entry program at Apex University is tailored for diploma holders and non-engineering graduates who aspire to advance their careers in data science. This program allows students to join directly in the second year, speeding up their academic journey. The curriculum covers essential areas such as data analysis, machine learning, statistical modeling, data visualization, and big data technologies. Students gain practical experience through hands-on projects, internships, and industry collaborations. Apex University ensures that graduates are well-equipped with the technical skills and analytical mindset needed to excel in the rapidly growing field of data science. This program prepares students for lucrative careers in data analytics, machine learning, and other tech-driven industries.
Course Details
Eligibility Criteria
Passed Minimum THREE years / TWO years (Lateral Entry) Diploma examination with at least 45% marks (40% marks in case of candidates belonging to reserved category) in ANY branch of Engineering and Technology.OR Passed B.Sc. Degree from a recognized University as defined by UGC, with at least 50% marks for general (45% marks in case of candidates belonging to reserved category) and passed 10+2 examination with Mathematics as a subject.
Fees Per Semester
65000/-
Duration / Schedule
3 Years (6 Semesters)
Seat Metrix
50% CUET and 50 % AUCET
SCHOLARSHIP AVAILABLE
Scholarship up-to 10 Lacs available for meritorious students
Check Eligibility
Programme Structure
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
Data Engineer:
Develops and maintains data infrastructure, integrates data sources, and ensures quality for predictive analytics and reporting.
Business Intelligence Analyst:
Uses data visualization and analytics tools to interpret business trends and provide actionable insights for companies.
Big Data Engineer:
Designs and maintains large-scale data pipelines, optimizes storage, and ensures efficient data processing for analytics.
Data Analyst:
Collects, processes, and interprets data to generate insights that drive business growth and decision-making.
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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