Tips for Successful Completion of Data Analytics and Machine Learning Course by Imarticus Learning

Tanmay Korlekar

07 June 2023

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Course Overview

Post Graduate Program in Data Analytics & Machine Learning is an Imarticus data science course developed by industry experts to help you learn real-world applications of Data Science from scratch and build powerful models to generate useful business insights and predictions. This program has been designed for fresh graduates and early career professionals (having 0-5 years of experience) looking to build their careers in Data Science and Analytics, a field in great demand.

The learners can take a big career leap with this data science course with a placement guarantee. They get guaranteed interview opportunities after completing the course. Mock exams and interviews are conducted by external faculties who are established professionals as Data scientists to help them prepare for the placements. Separate sessions are conducted to enhance the soft skills, resume and profile building for the interviews and overall career development. In these sessions, typical questions like "introduce yourself," where do you see yourself in 5 years," and what should be the appropriate answer to these questions are discussed.

The instructors for this PG program in Data Science include Alok Nagesh (who possess an enviable prowess in customer-centric analytics that enables him to influence data-driven business decisions at the highest levels of management), Gagan Lohar (who specializes in web development, Data Science and Hadoop), and Nikita Tandel (whose in-depth understanding of data tools like Python, SAS and Tableau, as well as her proficiency in AI and ML, distinguish her as one of the most ideal Data Science instructors around).

"Despite being a fresher in Data Science, I was able to assist my colleagues on live projects within a month of work, all thanks to this course."

- Tanmay Korlekar

Course Structure

This online certification is an advanced-level course. It requires an effort of 16 hours per week to complete the course, which is spread over 6 months. The best thing about this course is that the curriculum is limited and precise. The focus of the course is to impart knowledge about the basic terms or languages required in Data Science.

For example, a lot of focus was given to mastering Pandas and Numpy in Python, which forms the basics of all Data Manipulation processes. Majority of work in the industry revolves around google sheets, dealing with dates (formatting dates, accessing current dates), following proper coding standards, etc. All of these were also given equal importance in the course. This helps students get industry-ready.

The curriculum is designed to help you acquire the exact set of skills sought after by top companies. The course covered :

Basics of statistics - Measure of central tendency(mean, mode, median), probability distribution, basic terms used in statistics and probability
Programming languages - Python, MySQL, Pandas, Numpy, Seaborn, Matplotlib
Machine learning - ML algorithm theory, supervised learning, unsupervised learning
Deep learning - Neural networks, open cv
Visualization/Business Intelligence Tool - Tableau

Insider Tips

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

Pay Attention

Pay attention to the teacher and what he or she is teaching. If you have any doubts, get them solved at the very moment itself because many concepts are interconnected, and if you tend to miss one part, you might not understand the next part smoothly. In the online schema, the trainer usually shares his or her contact number, and email, which you could use to get in touch with them post the session to clear any doubts.

Assessment or Grading Criteria

Big Data is the lifeline of the tech world today, where companies are moving at lightning speed. This makes it important that the course integrates real-world use cases. In this Edureka course, each topic has a specific use-case that focuses on a high-paced industry dummy project which helps students to understand how the real-world project is implemented. Wherever students get stuck, the professors step in. Students can connect with them through email and over the call by raising tickets on the portal.

Doubt Sessions or Technical Support

The 24-hour technical support is icing on the cake. Each student is assigned a consultant who assists and guides them. Once you have raised the ticket, the technical team will reach out to you within a few hours solving technical challenges you are facing regarding installations or recording-related issues. As Edureka purely believes in hands-on training, technical teams will help students to get the course prescribed environment set up on their system. I faced a few challenges during installations but the Edureka tech team proved to be of great help.

Maintain a Github Repository

Try to post your project on Github regularly. A good Git-Hub profile definitely attracts lots of recruiters and it also keeps your work well arranged.

Final Take

I completed my Bachelor in Technology (B.Tech) in Mechanical Engineering and hence, I was finding it difficult to switch to a core technical IT job. Well, post this course, I was able to switch comfortably to my desired field. Despite being a fresher in Data Science, I was able to assist my colleagues on live projects within a month of work, all thanks to this PG course in Data Science.

In my current organization, we are using R for coding, whereas the course focused on teaching Python. Yet the course was designed so that I could not face any major challenges switching to a new programming language and could easily do it. The projects which were taken for practice in the course are similar to the live projects that I am currently working on. So, I would definitely recommend this course to someone who is looking for a data analyst course with a job guarantee.