Masters in Information Technology

Expand your knowledge of the concepts and techniques used in the information technology industry with the Master’s program. Drive and diversify your career.

Overview

Why Masters in Information Technology

Master’s degree in information technology prepares graduates for many in-demand career paths. IT careers are projected to see strong employment growth in the coming years. For instance, software developers’ job opportunities will increase by 22% nationwide from 2012 to 2022, while IT managers’ employment will rise by 15%, the U.S. Bureau of Labor Statistics (BLS) reports. By comparison, the average growth rate for all occupations is 11% during that same period.

 

Why Study in Sollers.

Sollers MSIT Program curriculum is very unique. The curriculum is designed to cover basics to advanced concepts like Computer Architecture, Computer Networking, Java Programming, Big Data Programming, Web development,  Azure Cloud Computing, Data Visualization, and Machine Learning. In the fourth semester, students have different electives to choose from. All the electives enable students to follow a career path in the fields they love in technology and earn a living. Here are the electives students can choose in Sollers.

  • Identity Access Management (IAM), Virtual Machine (VM) and Networking
  • Java Full Stack Development
  • Azure Full Stack Development
  • Big Data Analytics
  • Machine Learning and Artificial Intelligence using Python
  • Cloud Data Engineering

All our faculties have more than 20 years of experience. The faculties will groom the students from day 1 to help students launch a successful career. We want the students to succeed in their fields!

 

Learning Outcomes

Job opportunities:

According to the Bureau of Labor Statistics, computer and information technology managers’ job growth is projected to be 11% between 2018 and 2028. Sollers MSIT can help prepare you to be an:

  • IAM, Virtual Machine or Networking Engineer – Average Salary ~$81,000K – ~$139,000K
  • Big Data Engineer – Average Salary ~$117,766K
  • Java Full Stack Developer – Average Salary ~$119,892K
  • Azure Full Stack Developer – Average Salary ~$110,500K
  • Cloud Data Engineer- Average Salary ~$124,345K

In this course, our graduates will learn:

  • Use an integrated development environment to write, compile, run, and test simple object-oriented Java programs.
  • Hands-on activities focus on implementing techniques for efficiently managing and manipulating substantial data sets residing in a distributed SQL database.
  • Web Development – Angular High-level concepts, Modules, Components, and services will be covered. .Net core introduction and the high-level concepts of .NET Core API, Middleware, Routing, and Project and examples.
  • Knowledge of machine learning algorithms, neural networks, deep learning, support vector machines, tree-based methods, expectation-maximization, and principal components analysis.
  • Use ofvisualization design, data principles, visual encoding principles, interaction principles, single/multiple view methods, item/attribute, attribute reduction methods, toolkits, and evaluation.
  • Principles of Cloud Computing, Azure architecture & Service guarantees, Managing services with Azure portal.

Electives:

In the fourth semester, the students will have an option to choose the following electives.

  • IAM, Virtual Machine and Networking module will cover  the core concepts like Azure Active Directory, Storage, Azure Ad Connect, Users, Groups, VPC, Subnet, Networks, and Management
  • Java Full Stack Development module will cover the front end and backend of database and cloud technologies like Angular, Spring, JSP, Hibernate, AWS, Google Cloud, Postgresql, Cassandra.
  • Azure Full Stack Development includes .Net, SQL, C#, web development, Unit Testing, and Selenium. After the main course, students will have an option to choose the specializations:
    • Track 1 – Cloud Data Engineering
      • Data Catalog, Cosmos DB, Azure Data Factory, Data Lake
    • Track 2 – Azure Full Stack Web Development
      • Interface Development/Middleware development/Business Layer, Backend Development
    • Track 3 – SDET
      • Selenium – IWebDriver, IWebElement, FindElements, Dropdown and multi-select locators and XPath, Implicit and Explicit wait, Page Object Model, Data-Driven testing, WebElement Extensions
  • Big Data Analytics will help students think critically in making decisions based on data and deep analytics using Big Data. Students will demonstrate the ability to use technical skills in predictive and prescriptive modeling to support business decision-making.
  • Machine Learning and Artificial Intelligence using Python – Students will increase their expertise in the most widely-used AI & ML tools and technologies. The program helps to independently solve business problems and master the skills needed to build machine learning and deep learning models.
  • Cloud Data Engineering with Specialization of AWSwill cover the concepts like AWS Machine Learning, AWS Chatbots, Web Services, SQL and NoSQL, Aurora and Dynamo Databases, DWH modeling, Hands-on in Redshift,
  • PaaS vs. IaaS, AWS EMR, Lambda, Glue, and Kinesis.

Syllabus

Course Name

Credits

Semester – I

MSIT601 Principles of Database Systems Part 1

1

MSIT602 Programming Languages

2

MSIT603 Computer Architecture I

2

MSIT604 Introduction to Operating Systems

2

MSIT605 Computer Networking

2

Course Name

Credits

Semester – II

MSIT606 Principles of Database Systems Part 2

1

MSIT607 Java Programming Part 1

2

MSIT608 Big Data Information Systems

2

MSIT609 Web Development

2

MSIT610 Information Security

2

Course Name

Credits

Semester – III

MSIT611 Information Visualization using Tableau

2

MSIT612 Programing basics with Python

2

MSIT613 Machine Learning

3

MSIT614 Cloud Computing – Introduction to Microsoft Azure

2

Course Name

Credits

Semester – IV

EL615 – Electives

9

IAM Identity Access Management, Virtual Machine and Networking

JFS Java Full Stack Development

AFS Azure Full Stack Development

BDA Big Data Analytics

MLAI Machine Learning and Artificial Intelligence using Python

CDE Cloud Data Engineering

Total Credits

36

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

Reserve your spot

Limited seats only

Reserve your spot

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