Data Science and Big Data Analytics: Making Data-Driven Decisions

Data Science and Big Data Analytics: Making Data-Driven Decisions

Data Science and Big Data Analytics: Making Data-Driven Decisions

With the need for data on the rise day in day out, there is the need to create, handle, and analyze large datasets to get prized business insights. Organizations now look for ways to gain more value from the new data they create for their customers, processes, and industries on a day-to-day basis. The questions how do data scientists, professionals, and analysts turn extensive data into actionable insights, and how do they use data efficiently? These questions and several other questions can be adequately answered by individuals who have undergone the seven weeks Data Science and Big Data Analytics: Making Data-Driven Decisions online course. Big Data Analytics and Data Science: Making Data-Driven Decisions can also be called MIT XPRO.

Why should I study MIT XPRO?

MIT XPRO is a way to gain more knowledge of data technologies in a more professional approach in the MIT way. It hands individuals, companies, and teams professional development opportunities in leveraging on the latest learning technologies in achieving tremendous results with big data all in seven weeks. After the completion of the seven weeks online course that would take into consideration and accommodate your busy lifestyle, you would be awarded the MIT data science certificate and a 1.8 Continuing Education Units (CEUs).

How do I know the MIT XPRO course is for me?

Data science is comprehensive, and its information and use are not limited to a specific people, anyone who is interested in knowing how data science works and wishes to learn more about it can apply for the certification course. The course was developed for data scientists, analysts, and professionals, but individuals from all works of like can also take up this course if they wish to and get certified like the people listed above. The faculty in charge of the course advises that only people who are already comfortable with statistical techniques, data calculations, and quantitative methods of data research should put in for the course since it is not an introductory course. The course is thereof available for individuals who are early career professionals and senior managers. 

What would you gain after the completion of the course?

On the completion of the data science online Bootcamp, you would be learning how to do the following;

  • Identify and prevent common pitfalls in big data analytics and help in making better business decisions by interpreting analytical models
  • Techniques of data science to help manage the data management challenges in an organization
  • With the use of predictive analytics, you would be able to covert datasets to models
  • Recognize the problems associated with scaling big data algorithms
  • Understanding how to represent the data when making predictions
  • Determine the difference between network models and graphical models

Requirements for this course

Like many other courses, there are certain things and skills you need to possess before you participate in this course and get certified. You would be required to solve two case studies as assignments that you would answer with python. It is, therefore, necessary to have an idea of how to make use of Python 2.7 or 3.6, since there would be guidelines and instructions on how to use the language. It would be a plus to have an idea of Matlab as a few optional case studies require its use in answering the questions on them. There is no urgent need to know how to code as it is not that important.

Other requirements for this course include having access to the internet as the videos are only available by streaming it online as you are not given the option to download it. It is also essential for you to have the ability to download and read PDFs as those are the course materials to be used for preparation and learning in addition to the video lessons. You should have the latest version of Firefox, Chrome, or Safari browsers as our courseware works well on the newest version of any of the browsers listed. The use of mobile devices is no advised as not all components of the website can be accessed by a mobile phone. 

Cost of the course and the next date for the course

The price of Data Science and Big Data Analytics stands at $899, and it runs for seven weeks. The next date for the commencement of the course if February 3, 2020, as shown on our website. The lectures are available because they are pre-taped and can be followed or watched in your free time, provided you can do so and complete the assignments before the completion of the seven weeks. You would have a 90 days access to the archive course resources. The course requires a time commitment of 4-5 hours per week. It might be necessary at times to participate in the discussion forum along the way to get a better insight into the course. Should you register and decide to cancel your registration, you are free to do so but would not get a refund of your money after a particular date. All cancellation requests should be submitted to our sales team. The application should include your order number and your full name. The refund of the money would be charged back to the card used for payment and can take about two billing cycles before it is refunded.

How do I pay, and when would I get access to the course site?

To register, all you need do is complete the registration form and pay online with any of the recognized credit cards like the MasterCard, visa card, American Express, and others. There are no payment options, and as such, you are only expected to make full payments. Instructions on how to access the site would then be sent to all paid registered individuals via email before the launch date. If you do not receive the info by the start of the course, visit your dashboard to login and start the course.

What certification would I receive?

When you meet the requirement to pass the course, you will earn a professional data science certificate and 1.8 Continuing Education Units (CEUs) from our university.

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