Expand Your Job Opportunities in Data Analytics and Machine Learning Careers with this Imarticus Learning Program

Shubham Patil

07 June 2023

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Course Overview

PG Program in Data Analytics and Machine Learning, is unlike any other, as it is created in collaboration with the Data Science and Analytics industry itself. The program is specifically designed to teach you skills that are in great demand by the largest employers of Data Scientists around the world.

The program includes Capstone projects, real-world projects, case studies, and mentorship from faculty and industry professionals. Industry experts have created this PG program to teach you how to apply Data Science in real life and create powerful models that can generate business insights and predictions.

This program is for young professionals and graduates (with 0-5 years of experience) who are looking to advance their careers in Data Science and Analytics. This program guarantees a job placement.

"Doing the course helped me land a lucrative job as an ML engineer in a corporate firm."

- Shubham Patil

Course Structure

It is a self-paced, well-curated intermediate-level course spread over 6 months. This online course is taught by experienced faculty members. It usually requires learners to put in an effort of 16 hours per week in order to match the course pace. Nikita Tandel and Devdatta Supnekar were my instructors. The former was a soft-spoken and fluent faculty, and the latter’s concept delivery was exceptional. The course covers a lot of interesting subjects, with (usually) good explanatory videos and walkthroughs.

While doing the course, you will get a lot of hands-on experience writing code. The best part about this is that you will have a working code that you can tweak and use for your own projects and also a ton of ideas to work on afterward. Some of the top skills you will learn in the course are: R Programming, Tableau, Big Data Analytics, Data Science, Hadoop, Data Visualization, Power BI, etc.

Insider Tips

In order to get the best out of this course, below I have included some important tips that I think you might find useful.

Assessment and Grading Criteria

The assessment method requires completing assignments and undertaking projects under various modules throughout the degree. These can be research-based or concept specific. The evaluations are designed to ensure continuous student engagement with the program and to encourage learning. One could take the assessment a maximum of 3 times.

Hands-on Training

The course ends with a mini-Capstone which eventually happens to be an outcome of hands-on experience leverages provided by this curriculum concerning real-world projects and case studies. They even provided mentorship sessions at regular intervals during the course duration.

Final Take

Currently, I’m working as a ML Engineer in a corporate firm. I must say that the well-curated curriculum of this course was what helped me land this lucrative job in less time. I would recommend this course for novices to gain hands-on experience in working code that they can tweak and use for their own projects afterwards.