10 Best Ways to Learn Data Science and Prepare for Interviews

Spread the love

Learn Data Science

Data Science has not only become one of the most rewarding jobs in few years but also has grabbed a lot of eyeballs from students with varied streams. It is very important to brush yourself up for the right skillset from the right resources for the right job. Interviews are a big deal for everyone, and people usually confuse themselves while trying to get a job. In addition to that, it involves a lot of uncertainty, randomness, and human errors. A good portfolio most of the time helps you get the first call, and if you really know your thing, you are almost 90% there. The rest depends upon how one mixes it and gathers it as a personality for themselves. Here are the ten best ways to learn data science and prepare for the interviews along with it.

1. Develop the essential skills in Algebra, Statistics, and Machine Learning:

First things first, and let us not sugarcoat this. It is very essential to be technically sound if one wants to enter the world of data. Mathematics and computer science are two more essential subjects contributing to 85% of your data science journey. The rest, 15% is all about the domain that you are going to work in. It is essential to acquire skills in Algebra, ML, and especially in statistics. The base to learn data science starts with learning statistics. Statistics play an important role in the data science career. So learn it and have a proper balance in the 3 different skills.

2. Learn to love (Big) data:

Data scientists need to work on an enormous volume of processed and unprocessed datasets. It is not a hidden fact that data is very important. In addition to that, they use several big data software to accomplish shared processing. That explains the importance of big data. So, in the data science, learning journey one should also learn to explore big data. In addition to that, it also requires learning how to treat big data using tools like Hadoop, HPCC, Storm, Qubole, etc.

3. Certifications:

Once you have made up your mind to make a career in data science, you can explore and opt for the right online or offline certification programs in data science. Just be cautious about the online traps and analyze well before you enrol for the one that suits your requirement the best. Ivy Professional School’s collaboration with NASSCOM will unlock many opportunities for data science aspirants and help them towards an excellent career. The program endorsed by NASSCOM under this collaboration is Data Science & Machine Learning, Artificial Intelligence, and Deep Learning Certification Course. It includes high-demand tools like Python, R, Tableau, SQL, Adv Excel, VBA, etc., and you can apply here.

4. Gain a thorough knowledge of databases: 

In order to deal with enormous data being generated every moment, most of the data science service providing companies use database management software. One such software is MySQL, used to save and investigate data. Learn to get insight into the workings of this DBMS which will surely help to go a long way in securing your dream job in data science. If you are a fresher, you might check Kaggle, GitHub, Hackerrank in order to know about datasets and practice them.

5. Coding is important:

Practice makes one perfect. With reference to the above point, it is important one must keep practising the codes. Coding is important as you have to learn the basic languages in which data communicate. Before you analyze the data, it’s very important to be able to import and convert it into a machine-readable language. You may explore datasets as mentioned in the previous points and practice working with data. This will enhance your coding experience.

6. Learn the art of data preparation and visualization:

It’s very important to convert the data from the raw form to the easy to analyze form. The process of refining the data for use is called data munging. Also, it’s very important in the data science field to learn and master visualization skills. MS Excel is one of the most used tools for all kinds of data work, including data visualization. However, there are others like Tableau, Power BI, and Qlikview. This skill would come to a place only if one has enough knowledge about data and design. Having design knowledge helps identify the correct types of visualization that will help tell the story in a better way. Hence, we can surely say that data and design work together when it comes to data visualization.

7. Working on real projects:

It’s very important to keep on implementing what you have learned. That’s the best way to learn as it enhances practical knowledge. One must try working and implementing their learning on sample / real-time projects, and later you can add that to your portfolio. In addition to that, it can be a valuable thing to talk about in your job interviews. You can find internships online or work on random datasets from Kaggle, GitHub.

8. Be a team player and learn that skill:

Teamwork is the key to progress. Mostly, post-learning data science would be within a team, and you will need to be a good team player. When you are working together with a like-minded group, being observant will always help. This is also a top required and discussed skill in the interviews. Being a team player enhances your data science skills as you will learn how the team learns, adapts, and the various methodologies that they use to work on datasets.

9. Good communication is a must: 

In the data science world, there will be instances where your communication skills will be able to navigate you and your team through unforeseen situations. The better you can explain the visualizations, the more it will be beneficial for you. Also, good communication helps in expressing your views and analyzing business solutions. In most cases, it is essential to make everyone understand the data science activities in simpler language, which will only happen through effective communication skills.

10. Be a part of the Data Science Community and participate actively:

Follow and join data science communities and stay up to date and in sync with like-minded people. Data Science communities will help you to understand what’s currently trending in the market and will also provide you with the opportunity to learn with others. You can find various data science communities and blog posts to follow online. Later you can connect and help others to grow with you and can share your achievements and projects in your interviews.

Learn with Ivy:

Ivy Professional School has been consistently ranked among the top data science and analytics course institutes since 2008. Ivy has a pool of faculties who are industry experts with 10+ years of industry experience. It aims to provide specific learning experiences that organizations are looking for in their prospective data science candidates. If you are looking to get certified in Data Science and get recognized with your skills, we recommend choosing from our range of Data Science Certifications. You can also get in touch with us at +91-7676882222.

Spread the love

Leave a Reply

Your email address will not be published. Required fields are marked *

Paste your AdWords Remarketing code here