Learn AI and Data Science with a Low-Code Approach

Please note that submitting the registration fee does constitute enrolling in the program, and the below cancellation penalties will be applied. If you are unable to attend your program, please review our dropout and refund policies below:

• Dropout requests received within 7 days of enrollment and more than 42 days prior to the commencement of the program will incur no fee. Any payment received will be refunded in full.

• Dropout requests received more than 42 days prior to the program but more than 7 days after the acceptance are subject to a cancellation fee of USD 250.

• Dropout requests received 22-41 days prior to the commencement of the program are subject to a cancellation fee equal to 50% of the program fee.

• Any dropout requests received fewer than 22 days prior to the commencement of the program are subject to a cancellation fee equal to 100% of the program fee.

• No refund will be made to those who do not engage in the program or leave before completing a program for which they have been registered.

Candidates can pay the course fee through Bank Transfer and Credit/Debit Cards. They can also avail PayPal payment options.

For further details, please get in touch with us at adsp.mit@mygreatlearning.com.

This professional course costs USD 3900, which candidates can pay through Credit/Debit Cards and Bank transfers. For further details, please get in touch with the Great Learning team.

No. Through the Learning Management System (LMS), learners can access all the necessary learning materials online. There will be a list of recommended books and other resources for your in-depth reading pleasure because these fields are broad and constantly changing, so there is always more you can learn.

We welcome corporate sponsorships and can help you through the process. 

[For more information, please write to us at adsp.mit@mygreatlearning.com or +1 617 468 7899]

You should possess a working knowledge of computer programming and statistics.

The prerequisites of the program include working knowledge of programming and statistics. Suppose you do not possess either (or both) of them. In that case, you will have to put in extra effort to learn them before the program's commencement in order to cope with the curriculum designed by MIT Professional Education.

We, from Great Learning, will provide you with content that can be useful in understanding the fundamentals of programming (Python) and statistics. However, you would be required to put in extra effort and hours to complete the programming assignments.

The applications go through a rolling process that closes when the required number of seats in the cohort is filled. Please submit your application as soon as possible to boost your chances of getting a seat.

Candidates must fulfill the eligibility requirements listed above to enroll in this course. The following is the typical application procedure for those candidates who qualify:

• Step-1: Application Form

Candidates must fill out their online application form.
 

• Step-2: Application Screening

Upon receiving the application, the program team will review it to determine your fit with the program.
 

• Step-3: Program Enrollment

If chosen, candidates will be given an offer for the upcoming cohort. By paying the fee, they can reserve their seats.

Upon the successful completion of this program, learners become a part of MIT Professional Education's alumni community group and can access alumni benefits, that include a 15% discount towards any short programs offered by MIT Professional Education.

No, Data Science and Applied Data Science are different.

Data Science is a broad field that involves techniques and processes for gathering and analyzing data to generate insights, predictions, and strategies. It includes topics such as machine learning, artificial intelligence, and statistics.

Applied Data Science is the practice of using Data Science principles in different areas, such as e-commerce, healthcare, finance, and marketing. It focuses on utilizing data-driven approaches to design, develops, and deploy solutions to complex business problems. It focuses on the practical application of Data Science principles to derive insights and add value to different sectors of the economy.

The demand for Applied Data Scientists has seen massive growth over the past few years and is most likely to increase the graph in the upcoming years. Glassdoor’s research says that the Data Scientist role is the #3 job in the United States in 2022. According to a study by the U.S. Bureau of Labor Statistics, the demand for Data Scientists is expected to rise 36% by 2031, which is much quicker than the average for all the other occupations. Data Scientists are one of the fastest-growing jobs in the world.

Yes, Applied Data Science is absolutely worth it! Applied Data Science involves the application of Data Science principles and practices to solve real-world problems. With Applied Data Science, you can use data to inform business decision-making, optimize complex systems, and make products and services more effective. 

Applied Data Science is an essential skill that can help you stand out in the job market and give you the knowledge and skills to help your organization stay ahead of the competition. It can open the door to more job opportunities, more efficient systems, and better decision-making.

Numerous trending applications in the industry use Data Science. Some of the essential Data Science applications include:

• Healthcare Services: Data Science can be used in Medical Image Analysis like tumor detection, etc., using a Machine Learning Method, Support Vector Machine (SVM).
  
   
• Banking and Finance Sectors: Data Science can be used for fraud detection, risk modeling, customer data management, real-time predictive analytics, etc.
  
   
• Transport: Data Science is used in several cars, like optimizing vehicle performance, fuel consumption patterns, etc. It can also be used in self-driving cars for vehicle monitoring. For example, Uber uses Data Science and Machine Learning to predict the weather, availability of customers and transportation, etc.
  
   
• Manufacturing Industries: Data Science plays a vital role in the manufacturing industries, such as optimizing production, reducing costs, increasing profits, etc.
  
   
• E-commerce: Data Science can be used to identify customer base, predictive analytics for estimating goods and services, identify the latest trends of each product, optimize pricing of the products for customers, and many more.
  
   
• Image and Facial Recognition: Using Data Science and Machine Learning, you can identify a person in an image using a facial recognition algorithm. For example, when you upload a photo with your friends on Facebook, you get suggestions for tagging your friends in your picture. This automatic tag suggestion is an example of Image and Facial Recognition.
  
   
• Airline Sectors: With the help of Data Science, airline sectors can now predict flight delays, they can choose which class of airplanes they can buy to suit their specific needs, plan airline routes whether to take a halt in any place or put out a direct flight and many more.
  
   
• Gaming Sectors: In games, computers (opponents) collect data from your previous games and improve themselves in the upcoming games. For example, Chess.

There are several other industries that use Data Science for their applications.

Applied Data Science is a high/deep technical knowledge of how Data Science and its methodologies work. Applied Data Science involves modelling complicated problems, discovering insights, building highly advanced and high-risk algorithms, identifying opportunities through statistical and machine learning models, and visualization techniques for improving operational efficiency.

You can become an Applied Data Scientist by:

• Earning a bachelor’s degree in computer science, IT, mathematics/statistics, or any other Data Science related fields

• Gaining professional experience in Data Science by working at any organization

• Enrolling in an Applied Data Science Program from top universities, such as MIT, UC Berkeley, etc.

According to the research by Glassdoor, the average salary earned by an Applied Data Scientist in the United States is $125,784 per annum. The pay scale ranges from $83K per annum to $194K per annum.