Master of Science in Data Science

Learn how to apply the most in-demand tools such as Argus Oracle, Hadoop, SAS and more in the field of Data Science.

Overview

Why Data Science

Data scientists, data engineers, and business analysts are among the most sought-after positions in America. Yet, many existing and emerging workers don’t have the full skill set employers to need. A report from the US Bureau of Labour Statistics suggested that the rise of Data Science needs forecast to create roughly 11.5 million job openings by 2026.

Sollers’s Masters in Data Science is designed to the crater to the need of the emerging workforce. The programs focus on Basic concepts to Advanced concepts from Algorithms, Mathematical concepts, Statistics, Programming in R, AWS, Python, Data Visualization using Tableau, Modelling & Prediction, Information/Text Analytics, Machine Learning, NLP, Deep Learning using Python, and elective specialization tracks like

Track 1: Healthcare

Track 2: Fraud and Security Intelligence

Track 3: Forecasting and Econometrics

Our Graduates complete a capstone project by executing the core skills and concepts that combine the technical, analytical, interpretive, and social dimensions required to design and execute a full data science project. Students learn integral skills that prepare them for long-term professional success in the field.

The biggest advantage of studying in Sollers is most of our programs are customized based on industry requirements. Our career service advisors are Industry experts who support the students with resume and interview preparation to get ready for their career in Data Science.

Learning Outcomes

Job opportunities:

After completing the Masters in Data Science, you will have an opportunity to start a career as

  • Data Architect
  • Data Scientist
  • Data Modeler
  • Data Mining Analyst
  • Data Engineer
  • Data Developer

Students will learn:

  • Through collaborations and hands-on experience, you’ll immerse yourself in the fields of technology and build a comprehensive skill as a Data Scientist.
  • This Masters’s program will focus on areas like programming, statistics, data analytics, machine learning, data visualization, communication, business foundations, and ethics—this will increase your marketability in the fast-paced Data Science industry.
  • With a working knowledge of these in-demand technical skills and the soft skills employers seek, you’ll graduate prepared to apply your data science expertise to a wide range of industries.

In this course :

  • AWS- the core concepts of virtual private clouds, instance types, and storage services will be addressed and deeper architecture concepts.
  • Data Mining – Topics include the design and implementation of data warehouse and OLAP operations; data mining concepts and methods, such as association rule mining, pattern mining, classification, and clustering; and the applications of data-mining techniques to complex types of data in various fields. Advanced topics in machine learning and statistics will be covered.
  • Big Data Hadoop- Analytical approaches to handling the five Vs. — volume, velocity, variability, veracity, and value — of big data. Parallel programming based on the Map. Reduce paradigm within the Hadoop Ecosystem is used to address these needs.
  • Machine Learning – Solve problems in linear algebra, probability, optimization, and machine learning. Implement deep learning models in Python using the PyTorch library and train them with real-world datasets.
  • Data Visualization – Assess the quality of the data and perform exploratory analysis. Combine the data and follow the best practices to present your story.
  • The capstone project allows students to gain practical, real-world industry experience within their area of interest and use their new knowledge before graduation.

Syllabus

Register now, to get the complete syllabus.



    INSTRUCTORS

    Our instructors are not just highly experienced in the industry, they give you the personal attention you need and guide you every step of the way.

    Course Duration

    Starting soon

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    Limited seats only

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    For information regarding fee and/or reserving your spot, contact our Admissions Team.

    Credit transfers applicable for alumni

    OUR STUDENTS WORK AT

    Sollers partners with industry-leading corporations and provides them with ready-on-day-one employees. We record an 82% placement rate within three months of graduation.

    Financial Options

    Sollers has devised viable financial options for you to ensure tuition does not get in the way of your education. Now, you can focus your attention where it needs to be – in the classroom!

    Career Guidance

    After the completion of program, we assist our students with interview coaching, resume building sessions, conduct mock interviews, job readiness training and make them competent to venture into the corporate world.

    We provide exclusive one-on-one sessions with our industry-based career advisors who provide guidance right from resume feedback, assisting with interview Q&As, and helping with job preparations.

    Student Testimonials

    • Purvesh D.
      Sollers provided me a great opportunity to start my career in Big Data. The teaching faculty has very good experience and helped me out with any difficulties I faced during the course. I have worked on different Big Data technologies via projects. I recommend this course to aspiring students who want to kick start their careers in Big Data.
      Purvesh D.
    • Mehta M.
      My overall experience with Sollers was good. I got my first full-time job through their IAM training program. The faculty and Student Services are helpful and respond to your queries quickly. I got the opportunity to learn Active Directory and Microsoft Azure.
      Mehta M.

    Campus Visit

    FAQs

    It’s a full time two year program.

    The program is suitable for working recent undergraduates wishing to make their career in data science domains, undergraduates or graduates having some years of experience in IT/software domain or working executives looking to enhance their skills or make a career shift in data science domain.

    The prerequisites for the course is at least a bachelor’s degree in STEM discipline or bachelor’s degree in some other field with some years of experience in either a functional, IT or related field. The students should have some basic conceptual understanding of types of data, data structures, some analytical knowledge, preferably some programming language or tool.

    Students will gain hands on experience on the domains of data science which will include knowledge of programming languages, analytical and visualization tools and the core statistical and applied concepts which forms part of the data science domain. These would include programming languages like Python and Java, Big data ecosystem, visualization tools (both open source as well as commercial) and applications like Machine Learning, Natural Language Processing, Artificial Intelligence, etc.

    The growing demand and consumption of data have resulted in the surge for professionals who could analyze and work with different kinds of data. There exists a massive demand-supply gap in the domain of data science and big data. A research study conducted by Accenture found that more than 90% of clients planned to hire workers with DSA expertise, but 40% were confronted by a lack of available talent. Barring a few most position in Data Science domain demands a masters degree, thus this Masters Course is apt for professionals and students looking to make a career in data science domain.

    Industry Facts

    • IDC estimates that by 2020, business transactions (including both B2B and B2C) via the internet will reach up to 450 billion per day. Source : https://www.newgenapps.com/blog/big-data-statistics-predictions-on-the-future-of-big-data
    • Gartner estimates that 90% of large companies will have a CDO in a year’s time — with most of them learning on the job, according to the research firm.
    • By 2020, Forrester predicts businesses that use data effectively will be collectively worth $1.2 trillion, up from $333 billion in 2015