M.TECH-DATA SCIENCE AND BIG DATA ANALYTICS
Master of Technology in Data Science and Big Data Analytics
BEST UNIVERSITY FOR M.TECH-DATA SCIENCE AND BIG DATA ANALYTICS IN ROORKEE, UTTARAKHAND
M.Tech in Data Science and Big Data Analytics is a postgraduate program that provides students with advanced knowledge and hands-on experience in managing, analyzing, and interpreting large datasets using cutting-edge tools and techniques. The program covers key areas like data science, big data technologies, machine learning, data mining, artificial intelligence, and statistical modeling to enable students to extract actionable insights from massive datasets.
This M.Tech program equips students with the expertise to handle the challenges of working with big data, including data storage, processing, and analysis. Students learn how to use tools such as Hadoop, Spark, SQL, NoSQL databases, and cloud computing platforms to process and analyze large-scale data. With a focus on data visualization, predictive analytics, and business intelligence, graduates are well-prepared to make data-driven decisions in industries like finance, healthcare, retail, e-commerce, and technology.
The M.Tech in Data Science and Big Data Analytics program prepares students for high-demand roles like data scientists, data engineers, big data analysts, and business intelligence experts, helping them thrive in the rapidly evolving world of data analytics and big data technologies.
- Data Processing and Analysis: Teach students how to process and analyze vast amounts of data using big data technologies like Hadoop, Spark, and SQL.
- Machine Learning and AI: Provide expertise in applying machine learning and artificial intelligence techniques to solve real-world problems.
- Data Visualization: Develop skills to visualize complex datasets and present actionable insights for business decision-making.
- Predictive Analytics: Enable students to build predictive models to forecast trends and optimize business operations.
- Big Data Tools: Familiarize students with essential big data tools and platforms, ensuring they can work with large-scale data processing systems.
- Industry-Relevant Applications: Equip students with the ability to apply data science and big data analytics in industries like finance, healthcare, and e-commerce.
- Educational Qualification: Applicants must have a B.Tech or B.E. degree in Computer Science, Information Technology, Electronics, Mathematics, or related fields from a recognized university.
- Minimum Marks: A minimum of 50-60% aggregate marks (or equivalent CGPA) in the undergraduate degree is generally required, although this may vary by institution.
- Entrance Exams: Candidates must qualify for national entrance exams like GATE or university-specific exams to be considered for admission.
- Work Experience: While not mandatory, prior work experience in data science, big data technologies, or related fields can be advantageous for admission.
Click here for a detailed Fee Structure.
Course Highlights
Course Benefits
Career Opportunities
Collaborations
Course Highlights
- Comprehensive Curriculum: Covers core topics like data science, big data technologies (Hadoop, Spark), machine learning, predictive analytics, and data mining.
- Industry-Relevant Tools: Students gain hands-on experience with big data tools such as Hadoop, Spark, SQL, and cloud computing platforms.
- Practical Learning: Emphasis on real-world projects and case studies to build problem-solving skills in data analytics and big data processing.
- Advanced Techniques: Focus on advanced machine learning, data visualization, and statistical modeling to extract insights from large datasets.
- Career-Ready Skills: Prepares graduates for high-demand roles in data science, big data analytics, and business intelligence across various industries like finance, healthcare, and technology.
- Research Opportunities: Provides opportunities to engage in cutting-edge research in data science and big data analytics.
Course Benefits
- Industry-Ready Skills: Gain practical expertise in big data tools like Hadoop, Spark, and machine learning algorithms, preparing students for high-demand roles in data science and big data analytics.
- Hands-On Learning: Opportunities to work on real-world projects and case studies, enhancing problem-solving and analytical skills.
- Lucrative Career Opportunities: Graduates are in high demand across industries such as finance, healthcare, e-commerce, and technology, with the potential for competitive salaries.
- Advanced Techniques: Learn cutting-edge techniques in predictive analytics, data mining, and statistical modeling to extract actionable insights from large datasets.
- Research & Innovation: Exposure to the latest advancements in data science research, allowing students to contribute to innovative solutions.
- Global Career Prospects: Prepare for global career opportunities with top companies and research institutions seeking skilled professionals in big data and data science.
Career Opportunities
- Data Scientist: Analyze complex data to extract meaningful insights and help organizations make data-driven decisions.
- Big Data Engineer: Design and implement systems for managing and processing large datasets using technologies like Hadoop and Spark.
- Machine Learning Engineer: Develop and deploy machine learning models to solve real-world problems in areas such as finance, healthcare, and e-commerce.
- Data Analyst: Interpret and analyze data, create reports, and provide actionable insights for business improvement.
- Business Intelligence (BI) Analyst: Use data analytics tools to analyze trends, forecasts, and support business strategies.
- AI Specialist: Develop artificial intelligence applications, leveraging machine learning, deep learning, and data analysis techniques.
- Data Architect: Design and maintain databases and infrastructure for managing large-scale data efficiently.
- Analytics Consultant: Provide expert advice to organizations on optimizing their data and analytics processes.
Collaborations
The program is supported by partnerships with leading companies and organizations in the tech industry. These collaborations ensure that the curriculum is aligned with industry standards and provide students with opportunities for internships, mentorships, and live projects. Some of the key collaborators include:
- IBM Eduskill: Empowering students with industry-relevant training and certifications in cutting-edge technologies.
- Samatrix: Delivering specialized modules and hands-on learning in cybersecurity and blockchain.
- IBM SkillBuild: Providing a platform for mastering essential technical skills and practical expertise in emerging technologies.
- Blockchain startups and enterprises driving innovation.
- Academic alliances with global institutions for knowledge exchange.
PLACEMENT
CAREER PROSPECTS
A Master of Technology (M.Tech.) in Data Science and Big Data Analytics offers vast career prospects in the growing fields of data analysis, artificial intelligence, and business intelligence. Graduates can pursue roles such as data scientists, big data engineers, business analysts, machine learning specialists, data architects, and AI consultants in industries like finance, healthcare, e-commerce, marketing, and technology. With the increasing reliance on data-driven decision-making and the rapid growth of unstructured data, the demand for professionals skilled in big data processing, predictive analytics, and machine learning techniques is soaring. This program provides students with advanced knowledge of statistical modeling, data visualization, data mining, and machine learning algorithms, preparing them to harness big data to solve complex problems and drive business growth. M.Tech. in Data Science and Big Data Analytics graduates enjoy strong career growth, high earning potential, and the opportunity to work on groundbreaking projects that shape the future of industries through data-driven innovations.
FAQs
M.Tech in Data Science and Big Data Analytics is a postgraduate program that focuses on advanced techniques and tools used for analyzing and processing large datasets. The program covers areas such as machine learning, big data technologies like Hadoop and Spark, data visualization, and predictive analytics.
To be eligible for M.Tech in Data Science and Big Data Analytics, candidates must have a B.Tech or B.E. degree in Computer Science, Information Technology, Mathematics, or related fields. A minimum of 50-60% marks in the undergraduate degree is typically required. Some institutions may require candidates to clear entrance exams such as GATE or university-specific tests.
The M.Tech in Data Science and Big Data Analytics program typically takes 2 years to complete, divided into four semesters. The duration may vary depending on the institution and the structure of the program.
Graduates of M.Tech in Data Science and Big Data Analytics can pursue careers as data scientists, big data engineers, machine learning engineers, data analysts, business intelligence analysts, and AI specialists. These professionals are in high demand across industries like technology, finance, healthcare, e-commerce, and retail.
Key subjects in M.Tech in Data Science and Big Data Analytics include machine learning, data mining, Hadoop, Spark, big data architecture, predictive analytics, data visualization, and statistical modeling.
Graduates of M.Tech in Data Science and Big Data Analytics can expect an average salary ranging from INR 6-15 Lakhs per annum. With experience and expertise in advanced machine learning or big data technologies, salaries can exceed INR 20 Lakhs annually, especially in top-tier tech companies.
Job roles for M.Tech in Data Science and Big Data Analytics graduates include:
- Data Scientist
- Machine Learning Engineer
- Big Data Engineer
- Data Analyst
- Business Intelligence Analyst
- Data Architect
- Research Scientist
* For further details, refer to T&C Click Here.
The University offers hostel facilities with designated residential blocks for both boys and girls, available on a first-come, first-served basis. Accommodation is provided on a triple-sharing arrangement. Students who wish to avail themselves of on-campus hostel facilities are required to deposit the fee in advance.