Data Science Courses (Online and Hybrid)

Thanks to Great Learning for making my journey from a non-coding Mechanical Engineer to the Machine Learning field possible. I'm happy to share that I have been placed at DhiOmics Analytics as an ML Scientist. Through the program, I gained a lot of knowledge about Python, NumPy, Pandas, SQL, Tableau, ML models and more. I felt very engaged with the modules, assignments, Capstone Project and quizzes. The experience was very interactive, lively, easily understandable and well-structured. The teachers were very professional in their delivery and offered continuous support from the beginning to the end.

My experience with Great Learning was amazing. I come from a non-technical background but because of this program, I learned how to build linear regression models. I now understand the impact this type of tool has on practical applications. This program has given me an advantage in the workplace. I believe that I will be ahead of the curve when it comes to offering solutions to complex business problems. It has helped me build a strong foundation in Data Processing, constructing algorithms and using Python.

I always wanted to be associated with the business side of things, and hence decided to pursue this program for my upskilling journey. I found the curriculum extremely well-structured and focused on real-world applications of Data Science and Business Analytics. My overall experience has been great and I must say that the entire learning process was seamless.

With 25 years of experience as a technology leader, I took up this program to expand our company's services portfolio with analytics and machine learning capabilities. The program provided quality material and practical case studies, which helped me understand the concepts quickly and build working predictive models. The curriculum was well-organized, and the key takeaways for me were the steps of any Data Science project, how to perform them, identify relevant techniques, assess data quality, construct different kinds of predictive models, tune them, and use industry-standard tools such as Jupyter, DataSpell, and Google Colab.

Back in 2020, I was working in a reputed organisation. However, I lost my job shortly owing to the massive layoffs that were happening due to the pandemic. There were not many openings suitable for my role in any organization and I was under the stress of finding a new job. One day my father-in-law suggested that I make a career change and shift to Data Science as it was an upcoming and in-demand domain. He suggested a course by Great Learning. I gave some thought to it and decided, instead of wasting my time let's upgrade my skill set by learning something new. I started this course with a ray of hope that it will open some new opportunities for me but also there was fear at the back of my mind that I am investing money in this, and what if it doesn't work? But as the course began in September 2020, the syllabus was designed in such a manner that even a non-coder like me could easily grasp the concept and implement it. The different modules, assignments, quizzes, and projects all helped me a lot. Today, with great joy, I would like to inform you that I have managed to make a move into the Data Analytics domain. This transition happened when I managed to crack an interview with a very well-known organisation which is one of the Big 4 companies (Ernst & Young). It's been a little over a month since I stepped into this new role. I would like to thank the entire Great Learning team and also my family for their support.

Completing the MIT Applied Data Science Program was pivotal for me. With a background in Statistics and Mathematics, I sought to refresh my skills and stay current in Data Science. The program's intensity pushed me to excel, and its intuitive platform and responsive support made the journey seamless. I mastered Python coding for data analysis, visualization, and Machine Learning, enhancing my capabilities as a Data Scientist. Now, equipped with deeper insights into ML and data-driven decision-making, I confidently contribute to projects as a Product Owner, bridging technical expertise with stakeholder needs.

I recently completed the Data Science and Business Analytics PG program and found it insightful and informative. The program contents are detailed, and the videos comprehensively understand data analytics and its applications in business contexts. Additionally, the mentorship sessions helped enhance my understanding and clarify any doubts. The program also helped me improve my data visualization skills, and I now know the right and best plots to visualize datasets.

The MIT applied data science program was truly remarkable as it provided us with the opportunity to get insights from industry experts and apply that knowledge through hands-on projects. It was an amazing experience as we delved into learning a new programming language. Witnessing our fluency grow to the point where we could proficiently analyse various scenarios was particularly rewarding.

I'm immensely grateful for the transformative journey I've had in the MIT Applied Data Science program over 12 weeks. Starting with Python basics, we delved into Data Science essentials, statistical analysis, and machine learning. The support from faculty members and flexible project options made learning enjoyable. From deep learning to AI applications like Computer Vision and Generative AI, each module expanded my horizons. I can't thank MIT and Great Learning enough for this invaluable experience.

From my perspective, one potential downside was that the program was a bit too technical. However, I think it would be even better if there were more opportunities for hands-on application and practice of the concepts taught.