Data is the new petrol in the market right now. All the major businesses are dependent on the data. Terabytes of data are generated every second online. Organizations must find a way to handle, process, and store this data to grow in the market; this is where Data Science comes into the picture.
Data Science manages the data for the businesses in increasing their productivity and understanding more about the customer needs. With the demand Data Science has generated for itself in the industry it has opened up a multitude of job opportunities across the domains.
Let us understand now how to start your career in Data Science
How to Become a Data Scientist?
To become a Data Scientist, one needs to have at least graduation. Bachelors in computer science, social sciences, physical sciences, and statistics will give you skills to analyze big data. You can do a master’s in Data Science or join an online/offline Data Science training program.
A training program will equip you with all the advanced skills needed for the work environment. To master your skills, you can build an app, start a blog or learn more about Data Science strategies.
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Is Data Science a good career?
It is no doubt a great career choice. In fact, according to the US Bureau of Labor Statistics, it is one of the fastest-growing and high-paid jobs.
What kind of jobs can you get in Data Science?
Every field has data, and where there is data there is a scope for Data Science. Few industries that have been booming after the emergence of Data Science are retail, health care, banking, financial, IT, and many more.
Technical skills you need to learn for job
1. R Programming
Although prior knowledge of programming languages is not a must, basic programming knowledge will give you an edge while doing the course. R designed for Data Science needs. If you are new to it, then no need to worry, it is easy to learn.
Similar to the R programming knowledge, Python coding is not a must, but prior knowledge will help you. Python is a favorite among Data Scientists. It is easy to learn and has an online support community and library. It will take no time to master.
3. Hadoop platform
Unlike the above two, it is just an additional skill to give weight to your resume. Pig and Hive experience will also increase your chances of getting hired more. Cloud and Amazon S3 are a big addition.
4. SQL Database/Coding
As a Data Scientist, you need to write and execute queries in SQL, because SQL is designed for handling data. It can also help you in carrying out analytical functions and transforming database structures.
5. Apache Spark
Just like Hadoop, Apache Spark is a big data computation framework that is very popular among Data Scientists. It helps to run complicated algorithms faster. Hadoop is slower because it reads and writes to disk, while Spark caches its computations in memory. It also helps to prevent data.
6. Machine Learning and AI
Data Science requires you to work on a humongous amount of data and being familiar with ML and AI tools is always beneficial. As a Data Scientist, you need to work on neural networks, reinforcement learning, adversarial learning, etc. ML and AI tools knowledge is a great advantage.
7. Data Visualization
Data Visualization helps businesses to work directly with Data. Data visualization tools like ggplot, d3.js, Matplottlib, and Tableau help simplify complex results giving output. With the help of Data Visualization, a Data Scientist can quickly grasp the insights making it easy to react fast to business opportunities and stay ahead in the market.
8. Unstructured data
Unlike traditional data, unstructured data does not fit into any database tables and a Data Scientist needs to work with unstructured data from time to time. Examples of unstructured data include videos, blog posts, customer reviews, social media posts, video feeds, audio, etc. Streamlining unstructured data is difficult and hence needs tools to do it. Click here to learn data science course in hyderabad
Non-Technical skills needed for the job
1. Communication skills
Originations are looking for Data Scientists with good communication skills, Data Scientists required to make decisions according to the need of their non-technical colleagues to deliver the data. Having good communications skills makes it easy to understand and work with all the departments in an organization.
As a Data Scientist, one needs to work with many departments and teams in an office and new strategies and new products have to be developed. Teamwork is a must to excel in this prospect as Data Scientists need to interact with executives, engineers, product managers, and clients.
3. Business acumen
It is vital to understand the industry you are working in and should be able to solve problems the business is facing. With a good understanding of the business, you can put your efforts in the right direction.
Navigate to Address:
360DigiTMG – Data Science, Data Scientist Course Training in Bangalore
No 23, 2nd Floor, 9th Main Rd, 22nd Cross Rd, 7th Sector, HSR Layout, Bengaluru, Karnataka 560102
Salman Zafar is a serial entrepreneur, digital marketer, writer and publisher. He is the Founder of Techie Loops