Is a Data Science Course Hard?

It is no secret that Data Science is the most booming field in today’s field. It is considered to be one of the most demanded domains. A Data Science Certification can take you to places full of success and opportunities.

We live in a data-driven world; a Data Scientist is required to work on data and carry out operations. Hence, everyone from students to working professionals wants to pursue a career in Data Science.

What Data Science is All About?

Data Science is the process of gathering data, analyzing, filtering, and cleaning it to derive the most authentic and precise outcome. This process is carried out with the help of techniques such as Machine Learning, Deep Learning, Data Visualization, Statistical Analysis, etc.

Now, after learning the gigantic names of these techniques, you might fear if Data science is hard to learn. However, it’s just the names that may scare you, once you start with the course, it will pique your interest in learning more.

Let’s debunk all the myths revolving around taking up a Data Science Course.

1) You Need to Have A Strong IT Background.

False. Yes, some institutes have a preference for students who acquire prior coding or programming experience but many IT institutes like Itvedant provide Data Science courses for beginners as well.

Itvedant welcomes students with a non-IT background as well as students who have the basic skills and want to make it big in the IT Industry. However, if you have a good foundation in mathematics, statistics, and programming, it can be one step easier for you but if you have a strong desire to learn Data Science, you can become proficient in it quickly.

2) Getting a Job is Difficult in the Field of Data Science.

This entirely depends on where you are enrolled at. Not every Institute provides job or placement assistance. Speaking of which, institutes like Itvedant make their learners job-ready within 6 months after joining their Master’s in Data Science Course. Apart from that they also conduct profile-building sessions, mock interviews and organize job fairs.

If you have Data Science Certification from the finest institutes, you need not worry about job pitching. All you have to do is improve your skills and understand the concepts thoroughly.

3) You Need to Have A Science Background to Undertake a Data Science Course.

False. There is no such rule. You can enrol in a Data Science Course even if you belong to an Arts or Commerce background. What educational stream you belong to does not matter. You can take up a Data Science Course if you’re interested in pursuing a career in the IT field.

4) There Are Only Limited Job Titles in IT Industry.

False. There are numerous job titles in the IT Industry. Below we have listed some of the designations from the vast field of Data Science.

1) Data Scientist

2) Data Analyst

3) Machine Learning

4) Business Intelligence Analyst

5) Data Engineer

6) Big Data Analyst, etc.

5) Institutes Only Teach the Basics in the Data Science Course.
It is false because Itvedant has an extensive and advanced curriculum that updates now and then. Below we have mentioned the concepts covered in the Data Science Course. This is the curriculum of Itvedant’s Master’s in Data Science & Analytics with AI Course. It is for you to get to know what you can expect to learn once you enrol in the course. Their industry-level projects will help you learn each concept practically.

Curriculum:

1) Basics of Data Science and Data Analytics

2) Advance Excel

3) SQL

4) Machine Learning

5) Deep Learning

6) Analytics with Python

7) Python Programming

8) PowerBI and more…

Yes, the syllabus is even more diverse.

There’s no need for you to search Data Science Course and Data Analyst Course separately because Itvedant’s Master's Course in Data Science and Analytics with AI has got it all covered for you.

To sum up, Data Science is not a field that one can’t crack or get into. The right amount of skills and knowledge will help you make it big in the IT Industry. Remember, Data Science is a field that does not need hard work, it needs smart work.