Learn How to Make AI-Driven Decisions

The eligibility criteria for this program are as follows: 

• Early-career professionals or senior managers (IT Managers, Business Intelligence Analysts, Data Science Managers, Management Consultants, and Business Managers) who want to apply AI, Data Science and Machine Learning techniques in their firms. 
• Data Scientists, Data Analysts, or Business Analysts who wish to turn vast volumes of data into valuable insights 
• Entrepreneurs interested in innovation with the assistance of AI,Data Science and Machine Learning techniques 
• Those with academic or professional training in Applied Statistics or Mathematics will find the program easier to learn. However, participants without such a background can also complete the program, provided they are ready to put in extra effort. Great Learning will offer the required assistance.

A successful AI and Data Professional needs a firm grasp of coding skills. Here are the key skills that help a professional learn data science: 

Python: Python is the most widely used language in the field of data analysis and machine learning. 

Foundational Knowledge of Other Languages: Familiarity with R, SQL, and SAS is essential, especially for statistical analysis and database management. Some roles may also require exposure to Java, Scala, or Julia. 

Understanding of the Data Workflow: Beyond programming, you’ll need to know how to work with tools for data acquisition, cleaning, transformation, warehousing, and visualization.

The registration process for this AI and data science program is as follows: 

Step 1: Applicants will need to complete their online application form. 

Step 2: On receiving the application, the Great Learning program team will review it to determine your fit with the program. 

Step 3: If selected, you will receive an offer for the upcoming cohort. 

Step 4: Secure your seat by paying the fee.

The applications follow a rolling process, which is closed when the requisite number of seats in the cohort is filled. 

To ensure your chances of securing a seat, we encourage you to apply as early as possible.

Please refer to the fee section for details.

We accept corporate sponsorships and can assist you with the process.

[For more information, please write to us at dsml.mit@mygreatlearning.com]

Please note that submitting the registration fee constitutes enrollment in the program, and the cancellation penalties outlined below 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 registered.

You can pay the program fee via bank transfer or credit/debit card. You can also pay in easy installments and get interest-free payments for up to 12 months (Note that standard terms and conditions apply to these transactions).

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

Yes, the future of AI and Data Science is highly promising. As organizations become more AI and data-driven, the demand for professionals who can turn raw data into strategic insights is growing. Here’s why: 

Growing demand in Business: Companies are leveraging AI and data science to reduce costs, improve marketing effectiveness, launch better products, and tap into new markets. 

Data-driven strategy making: Gartner has forecasted that many corporate strategies will highlight data and analytics as essential business competencies.

Expanding applications: From healthcare and finance to retail and tech, AI and data science is shaping decision-making and driving innovation across industries. 

Career longevity: With data at the core of digital transformation, professionals with expertise in AI, ML, and data science are well-positioned for long-term career growth. 

As industries increasingly rely on data to drive innovation and growth, the need for skilled Data Science professionals will only continue to rise. 

Gaining expertise in Artificial Intelligence, Machine Learning and Data Science, is a smart investment for you to future-proof your career.

Nowadays, many organizations are using advanced Machine Learning and Data Science applications to draw the best outcomes for their businesses. Let's explore how data science and machine learning can benefit them: 

Provide solutions to develop the best business plan that supports companies' exponential growth. Today, most top-notch companies are applying Data Science and Machine learning in projects and operational management to achieve better outcomes. 

Shape businesses to suit the requirements of end customers. Businesses with a clear vision and expertise in data can develop groundbreaking solutions. Data-backed approaches enable companies to add value to their products and adapt latest market trends. 

Reduce costs of the businesses. Small and medium-sized companies strive for endurance due to limited budgets and resources. AI, Data Science, and ML help in formulating cost-effective business solutions.

The average salary of an AI professional is USD 175,000. For a Data Scientist, it is USD 130,000, and for a Machine Learning Specialist, it is USD 115,000.

To become a Data Scientist, you need to have a blend of technical expertise, analytical thinking, and real-world problem-solving skills. If you have a strong academic background, that will help you learn the concepts related to the field. 

Here’s how you can start: 

Build a strong foundation in mathematics, statistics, and programming. 

Gain hands-on experience with tools used in the industry. 

Develop applied knowledge through projects that simulate real-world data challenges. 

Strengthen your understanding of Generative AI, AI, and Machine Learning techniques.

Yes, there is an increasing demand for AI, Data Science, and Machine Learning professionals across a wide range of industries, including Technology, Healthcare, Cybersecurity, Finance, Oil & Gas, Transportation, Education, Talent Acquisition, Inventory Management, E-commerce, and more. 

As organizations increasingly adopt AI and data-driven decision-making, professionals skilled in AI, Data Science, Machine Learning, and Generative AI are in high demand. These skills offer strong opportunities for career growth, leadership roles, and long-term industry relevance. 

According to LinkedIn, hiring for Data Scientists saw a 46% increase in the last year. Employment of data scientists is projected to grow 36 percent from 2023 to 2033, significantly faster than the average growth rate for all occupations. If you’re looking to build a future-proof career, now is the time to upskill in AI, Data Science, and Machine Learning.

Data Science is a field of study that uses a scientific approach to extract meaningful insights from data. Meaningful insights are derived from data sets, generating knowledge that advises recommendations for business growth.