MS in Data Science Programme

A world class master's degree in data science from Northwestern University School of Professional Studies

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  • 18 Months
  • Live Sessions

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Why Choose This Programme?

World Class Education
  • Northwestern was ranked in top 10 U.S. universities (U.S. News & World Report 2020)
  • Designed and delivered by experienced faculty with industry experience.
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Comprehensive Learning
  • Learn not just theory but also popular programming languages, frameworks and libraries in a hands on environment
  • Capstone project to showcase acquired skills
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Career Assistance
  • Dedicated placement process for enrolled students
  • 1:1 Career mentorship, access to job boards and more
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Working Professional
Northwestern was ranked in top 10 U.S. universities (U.S. News & World Report 2020)
Career Support
Learn not just theory but also popular programming languages, frameworks and capstone project
Salary Hike
Dedicated placement process for enrolled students
Industry Project
Learn not just theory but also popular programming languages, frameworks

MS in Data Science Programme from Northwestern University

Online | 18 Months | Live Sessions

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A Comprehensive, World-Class Online Data Science Masters Degree  offered by Northwestern University in Collaboration with Great Learning

Data Science is one of the most sought after fields  in recent times. We have been hearing a lot about the revolution that this domain has been creating.  Many are aspiring to attain a data science master degree and get into the exciting job roles that this domain is offering. 

What is Data Science?

The aim of data science is to extract and interpret data effectively and present it in a simple language to the end users. In other words, data science can be defined as the application of tools and techniques to data to derive meaningful insights.

The availability of huge amounts of data and the improved processing capabilities have paved the way for the Data Science revolution across the world. 

Data Science has four important components. 

  • Data Cleaning- Cleaning of data deals with handling missing or incorrect input data.
  • Data Organising- Data organising refers to the process of classifying data and organising them to perform the necessary operations. 
  • Model Building- Model building involves the creation of prototypes. Several statistical tools and techniques are applied and the data is developed. The models are tested to ensure integrity of generated results. 
  • Data Delivery- Delivery of the data is nothing but ensuring that the most meaningful insights from the data are derived and the desired outcomes are delivered to the end-users. 

What are the various roles and responsibilities of a Data Scientist?

The demand for data scientists has been growing over the years with industries across the board recruiting for this role.

While they will need to have certain minimum common skills, the skillset and the expertise of data scientists working in different domains differ extensively. 

  • In order to be a successful and efficient data scientist one should be highly innovative and distinct in their approach to applying several techniques intelligently to extract data and derive the most meaningful outcomes. 
  • The main job role of a Data Scientist is to solve business problems and challenges. They should have the domain knowledge to understand business issues as well as industry standard terminology and workflows apart from data science skills.
  • Data Scientists must be efficient to locate and explore several data resources.
  • Data scientists must have hands on expertise with tools like R, Python to perform data conditioning which is converting the data into useful information by applying statistical analysis, predictive analysis and more.
  • A Data Scientist must be highly efficient in managing large amounts of data. 
  • A Data Scientist must be able to work effectively with a team and also possess effective communication skills to deliver knowledge to the members of the team precisely. 
  • Data Scientists deal with complex data problems and ideally should have some expertise in multiple disciplines. 

Job Roles in Data Science

If you are someone who is desiring to take up a data science course, you must learn about the various job roles that this domain offers. Below are a few job roles offered in the Data Science domain.

1. Data Scientist.

2. Data Administrator.

3. Data Analyst.

4. Business Analyst.

5. Analytics Manager.

6. Data Architect.

7. Business Intelligence Manager.

8. Statistician

9. Data Manager

Payscale of Data Scientists in the India

What is the salary scale offered for data science professionals in India ?

Latest technologies like Data Science have got immense demand for the benefits they offer.

The average pay scale of a data science professional in India is estimated as 7 Lakh per annum. A fresher who finished the data scientist course could expect a minimum of 5.5 lakh per annum. 

An experienced data science professional makes around 10 to 12 lakhs a year. Many multinational companies offer hefty packages that are way beyond the estimated packages for professionals working in this domain.

Applications of Data Science

The technology of Data Science has invaded many organisations and industries regardless of the domains. A lot more organisations are being enthusiastic about adapting this latest technology. 

Most organisations have realized the importance of data driven decision making. Many industries have witnessed the outstanding benefits that data science has been offering. Hence the requirement of data scientists is increasing exponentially across the globe. The domain of data science has attained an increasing demand like never before. In recent times, data science has become one of the crucial aspects of any industry or organisation. Data science is being employed in many domains such as marketing, engineering, production, sales, and more to make data driven decisions. 

Let us look into a few of the applications of data science in different domains:

  • Internet Search: All the search engines including Google use data science to deliver the most relevant search results in a fraction of seconds. Techniques like supervised learning help search engines identify useful search results as well as filter out spam. As the search industry matures, the data science techniques they apply also become more sophisticated Google wouldn't have been the google we are accessing today without Data Science. Data Science is considered as the backbone of internet search engines.
  • Marketing: The entire digital marketing spectrum starting from the display banners on various websites to the digital billing boards at the airports, are designed by employing the techniques of data science algorithms. Data Science has been the reason why digital ads are able to attain a lot of traffic than traditional marketing approaches. Digital advertisements are designed for the target audience by studying their past behaviors. 
  • E-commerce: The most popular e commerce websites such as Amazon, Netflix, Youtube, and more employ data science to suggest relevant products to their customers by studying their past behaviors. Data science recommendation systems not only help you find relevant products out of a billion products available with them but also enhances the user experience. Both the customers and the e-commerce sites get benefitted from data science. A lot more companies are fervently using data science recommendation systems to promote their products. Suggestions in accordance to user interests and relevance of information have taken their businesses to the next level.
  • Image Recognition: When you upload a picture on Facebook, it automatically suggests you tag your friends by recognising their faces. The automatic tag suggestion used by Facebook is made possible with data science. Scanning a barcode using the web browser using a mobile phone and many other features are the end results of data science. 
  • Speech Recognition: The best examples of data science speech recognition systems are Siri, Google Voice Assistant, Alexa, and more. When you aren't in a position to type a message, you can simply speak out the message and it will be converted to text. Speech recognition has been creating a revolution in designing smart homes. We see home electronics like window treatments, smart televisions, music players and more are being accessed at utmost ease with Google voice assistant and Alexa.
  • Healthcare Sector: Data science is observed to cause a revolution in the healthcare domain. The healthcare sector is accessing great benefits through data science. These include medical image analysis, personalised medical prescription, creation of drugs and more. Data science is assisting healthcare professionals to provide enhanced medical services to the patients by analysing the problem. 
  • Financial Industry: Data science aids the financial industry in fraud detection. Data science identifies the potential customers and eliminates fraudulent risks in the area of finance. It studies the past behaviour of the customer and ensures that no fraudulent activity is performed. 

Prerequisites of taking up a data science course

If you are keen about taking up the best online data science masters programs, you must also learn about the various prerequisites. 

Below are the basic skills you need to enter the world of Data Science:

  1. Statistics: Statistics is considered as one of the major prerequisites of mastering the technology of data science. Statistics is the study of collection, analysis, interpretation, and presentation of data. A data scientist must know statistics in order to perform the most crucial tasks of data science like data analysis. Descriptive analysis, probability theory, etc are the concepts of statistics that help the data scientists to make better data driven decisions from data sets. 
  2. Coding Skills: Programming languages help you to manipulate the data and apply certain algorithms that help you formulate meaningful algorithms. Python, R, Hadoop are a few of the programming languages employed by the data scientists. Python is the most widely used programming language and is also considered as the most popular one. Having a sound understanding of the desired programming languages would help you execute machine learning algorithms. 
  3. Data Extraction Transformation and Loading or ETL: The main job role of a data scientist is to extract the data from different data resources and convert it into a proper format for storing it for further use. You will have to store the data in the data warehouse to analyse the data. Hence having an understanding of Data extraction transformation and loading would help gain expertise in understanding the several concepts of Data Science. 
  4. Data Wrangling and Exploration: Cleaning and unifying the complex data sets for easy access and analysis is another important job responsibility of a Data Scientist. This process is termed as data wrangling. Exploratory data analysis helps to figure out the questions to be asked and derive solutions from the data sets. Hence Data Wrangling and Exploration techniques are also considered as one of the prerequisites of mastering Data Science.
  5. Machine Learning: Machine Learning is a subset of Artificial Intelligence. Machine Learning as the name suggests is the process of making machines more intelligent to study and learn by themselves. By developing efficient machine learning models, a data scientist will be able to derive the best solutions for several complex business problems. Machine Learning enables a Data Scientist to identify the most profitable opportunities and also avoid unexpected risks. Possessing a strong understanding of various supervised and unsupervised algorithms will assist you in becoming a successful data scientist.
  6. Deep Learning: Deep learning is a subset of machine learning. Deep learning has taken the traditional Machine Learning approach to another level. Deep learning is inspired by the human biological neurons through which neural networks are constructed to mimic the human brain. A large network of artificial neurons are employed to design a deep learning system. Deep learning enhances the efficiency of the solutions to be derived by a data scientist. Hence Deep Learning is also considered as one of the prerequisites of taking up the online data science masters course.
  7. Big data processing frameworks: A data scientist has to work with huge amounts of data to build machine learning and deep learning models. The data being generated and accessed is either structured or unstructured. Henceforth, it is necessary to employ big data processing systems to work with such humongous amounts of data sets. Big data frameworks such as Hadoop, Spark, and more would help data scientists to perform these tasks. In recent times, organisations ate employing big data analytics to acquire the most meaningful and hidden data insights. Therefore, possessing knowledge about Big data processing frameworks is considered as one of the must have skills to become a data scientist.
  8. Data Visualization tools: Having hands on expertise on Data Visualization tools is considered as one of the major prerequisites of learning data science. Data Visualization is one of the most crucial parts of Data Science. The tools of Data Visualization would help you present the data in the most understanding and visually appealing format. These tools would help you communicate better to the end-users. Gaining expertise in Data visualization tools such as Tableau, PowerBi, and more would be a great add on to learn data science.
  9. Problem solving skills: It is essential for a data scientist to possess good problem solving skills. Mastering different types of problem solving techniques and skills would enhance your efficiency as a data scientist.

Why Great Learning?

The job role of Data scientist has achieved immense traction in recent times and many professionals are striving to become one. Hence the demand for the Data Science courses has increased significantly. There are many institutes being sprouted on a daily basis that claim to offer the best Data Science courses. However, it is crucial to select the right one as it plays a vital role in shaping your career.

Great Learning is one of the most reputed organizations in the country that offers professional courses in the latest trending technological domains like Machine Learning, Data Science, Artificial Intelligence, Cloud Computing, and more. Hence, taking up the data scientist masters program offered by Great Learning in collaboration with the North Western University would surely stand as the best choice you could make to encounter a career breakthrough into the roles of Data Science. 

Northwestern University is ranked as one of the top 10 universities in the United States according to the U.S. News & World Report 2020. Hence taking up the data science masters course offered by the North Western University enables you to acquire the most in demand skills from a reputed institute which adds value to your profile. 

Below are the various advantages of taking up the Northwestern online masters data science program with Great Learning

Mentorship

A personal mentor, who is also an industry expert in data science will assist you throughout the course. Mentors will help candidates clear their doubts, resume preparation, interview workshops, and more.

Career Support

A dedicated process of placement assistance will be implemented for the students enrolled in the data science masters program. Great Learning's team will assist you in resume building. You will also partake in mock interviews and many other activities to get into the job of your dream. As Great Learning is associated with many top-notch companies across the world, candidates will be offered to take part in regular placement drives organized by Great Learning. The list of these companies includes Oracle, Deloitte, Accenture, EY, Honeywell, Cognizant, HP, Infosys, Tata Consultancy Services, and more. 

World-Class Faculty

You will be taught by the leading from top Indian and International institutions such as Harvard Business School, Stanford Graduate School of Business, Kellogg School of Business, University of Chicago, IIM Ahmedabad, IIM Bangalore, IIT Bombay, IIT Delhi, etc. Many of the faculty members of the MS in Data Science programme are  counted among the top 10 academicians of the country by Analytics India Magazine. 

Hands-on Learning

Even as you pursue the MS in data science programme , you will work on several real-life business problems and projects that help you gain practical insights into the techniques of Data Science. Through their interaction sessions, mentors will guide you on how to implement learnt concepts in real world conditions as well as share their experience from the data science domain. You will also be working on a capstone project that is perfectly designed by the industry experts to exercise all the techniques you have learned through the online classes and enhance your skills. The capstone projects are approved by the world-renowned Great Lakes Faculty and Northwestern University.

Flexibility

As the Northwestern University MS in Data Science programme is offered online, you will have the utmost flexibility to master data science. If you are an existing working professional, you do not have to give up on your current job, but learn data science in parallel. The live lecture sessions are  organized in such a fashion that they cause minimal disruptions to your personal and professional lives.

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