Learn How to Make AI-Driven Decisions

The eligibility criteria for this course are as follows:

• Working professionals like early-career professionals or senior managers (IT Managers, Business Intelligence Analysts, Data Science Managers, Management Consultants, and Business Managers) who want to apply Data Science and Machine Learning techniques in their firms

• Working professionals like Data Scientists, Data Analysts, or Business Analysts interested who wish to turn vast volumes of data into valuable insights

• Entrepreneurs interested in innovation with the assistance of Data Science and Machine Learning techniques

• Those possessing academic/professional training in Applied Statistics or Mathematics will find the course easier to learn. However, participants lacking this background will need to put in extra effort, and Great Learning will offer the required assistance

No. All the requisite learning material is provided online to learners through the Learning Management System (LMS). Considering these fields are vast and constantly evolving, there is always more you can learn, and there will be a list of suggested books and other resources for your in-depth reading enjoyment.

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 admission 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 registered.

Candidates can pay the course fee through Bank Transfer and Credit/Debit Cards. They can also pay in easy instalments using PayPal credit options and get interest-free payments for up to 6 months (Note that these services are subject to credit approval by PayPal).

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

Varying data resonates with one fact: The average salary of a Data Scientist and a Machine Learning specialist is well over USD 100,000. Indeed recorded an average annual salary of USD 142,858 for Machine Learning specialists and USD 126,927 for Data Scientists in the US. 

The list of industries incorporating data science and machine learning only continues to grow. The specialization commands authority across processes involved in Healthcare, Cybersecurity, Banking, Oil and Gas, Transportation, Education, Talent Acquisition, Inventory Management, Recommendation Systems and Price Optimization among other key business insights. With its inherently adaptive nature, the world of data science and analytics is here to stay and those mastering the tools and techniques of its stand to advance their careers while being at the forefront of all innovation.

Complex algorithms and sophisticated tools make up a large part of a data scientist's day. In addition to data analysis tools, keeping up with the latest tools in data acquisition, data cleansing, data warehousing and data visualization is becoming increasingly important as the historically separate roles of data scientist and analyst become merged for increased efficiency. Python is the lingua franca of data science but knowledge of R, SAS, SQL, and sometimes Java, Scala, Julia among others must also be acquired at the foundational level itself. Technical soundness is a must for moving forward towards solutions while avoiding roadblocks.

A good academic background can always be a plus when you are embarking on your journey but there are certain specific skills that are essential to master the tools and techniques. The right combination of technical and non-technical skills is imperative to chisel out a career in Data Science and Machine Learning. 

Revisiting your mathematical and statistical abilities can be a good motivator to further your journey into a data science and machine learning specialization. While you must be experienced with programming, hands-on experience with Python, R, etc. will mark the beginning of your transition into data science. Effective data science and machine learning course will not only commence with fulfilling these requirements for you but should be built to translate your learnings into a successful career with a comprehensive curriculum, also highlighting the role of a professional certificate in data science and machine learning.

Data Science roles have been among the most in-demand job roles in recent years. According to LinkedIn, hiring for data scientists saw an increase of 46% in the last year. The U.S Bureau of Labor Statistics has also predicted that the demand for data scientists is further expected to rise 27.9% by 2026. 

So, we are well within the age of Big Data and the decision making that it drives across industries for business growth. From enhancing leisure experiences such as filtering Netflix recommendations to suggesting a direction for legal policies, Data Science and Machine Learning are at the core of it all. By making holistic concepts now measurable and predicting something as grand as “how people will live,” data science shines with immense possibilities. Yet, all this data, with its unparalleled potential, is of little use unless the right minds are at work to process it. Employers worldwide thus realize the importance of data scientists and machine learning specialists and even encourage a “culture of analytics” that we see emerging in workplaces today

Organizations, on unlocking the potential of data science, have been known to see increased efficiency on several fronts. These include finding ways to reduce costs, expanding into new markets, tapping on different demographics, analysing the effectiveness of marketing campaigns and ultimately, deciding on the new products and services that can be launched. This resonated in Gartner predicting that, “By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.”

The advancement of technology in various fields contributes greatly to the growth of industries. Hence, many businesses are using advanced Machine Learning and Data Science applications to draw the best outcomes. Let us understand a few of the benefits of these booming domains of technology.

Building better business strategies

By employing Data Science and Machine learning, organizations can develop the best business plan. Data Science and Machine learning provide solutions to come up with the best business plan that supports companies' exponential growth. Today, most of the top-notch companies are applying Data Science and Machine learning in projects and operation management to obtain better outcomes.

Better Research and Inventions

Organizations must be conscious of the latest trends in their market. A data-driven business team would shape their business in the best way that suits the requirements of end customers. A data-driven organization would learn current technological trends, plan a business strategy that delivers the best services. Businesses with a good vision and well versed in data can compose groundbreaking solutions. Data-backed approaches assist businesses to add value to their products by adapting themselves to the latest trends in the market by incorporating the latest technology.  

Cost Reduction

Cost reduction is one of the major benefits that Data Science and Machine Learning contribute to any business. Small and medium scale companies certainly strive for their endurance considering their limited budget and resources. Data Science and Machine Learning help in formulating business solutions that are cost-effective.

Therefore, taking up a certification course in data science and machine learning would fetch you the best career opportunities with several industries in the market.

Machine learning refers to a group of techniques used by data scientists that allow computers to learn from data. It is the underlying process allowing machines to learn from data which results in you getting all your recommendations and predictions from Alexa. From leisure to work, our lives are made easier with machine learning. 

The responsibilities of a machine learning specialist constitute a spectrum extending from the creation of machine learning models to retraining systems. A specialization in machine learning means acquiring the necessary tools and techniques for the most crucial AI subset. A holistic skill set here, therefore, is made up of exceptional technical skills as well as an inherent learning attitude. 

Data science is a field of study that employs a scientific approach to extract meaningful insights from data. Data science is a field that functions at more than one level. Meaningful insights are drawn from data sets, producing knowledge that helps in recommending apt actions for business growth. The knowledge derived from data science being at play is a combination of technology, statistics and trends in the business domain.

To enroll in this course, the applicants must meet the eligibility criteria mentioned earlier. The standard registration process for the eligible students 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 course.

• 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.