How to Start a Data Science Career?

How to start a career in Data Science: Detailed Guidance For Beginners
How to Start a Data Science Career?
Written By:
Rahul Dey
Published on

Data Science is one of the most demanding fields as companies and industries are relying more on data to make business decisions. A highly skilled and experienced Data Scientist is highly in demand. Let’s look at the guide for making a career in Data Science.

Understanding Data Science

Data Science is a subject that grew out of statistics and data mining. It is the practice of taking out valuable information from data by using various techniques such as statistics, machine learning, and other techniques.

Is Data Science a Good Career Path?

Data Science came into existence because of the rapid increase in technology and there is a genius need to make sense of the ever-changing data. The data professionals create algorithms that help translate data patterns into research that informs government agencies, companies, and other organizations. The field offers versatility and can be applied to various industries including retail, transportation, sports, entertainment, etc.

Skills Needed For Becoming a Data Scientist

To build a career in Data Science, a strong foundation is required where the user needs to develop skills and expertise in many areas.

1. Maths and Statistics- Strong knowledge in Maths and Statistics as data science requires a strong understanding of statistics and mathematics like algebra, probability, calculus, differentiation, etc. All these concepts will help in the interpretation of data efficiently.

2. ⁠Programming Languages- Mastering programming languages like Python, R, and SQL, will help in statistical analysis, management and query databases.

3. Analysis and  Manipulation of Data- Cleaning and Manipulation of data are one of the key skill sets. Tools like Pandas in Python and dplyr in R will help in processing Raw data to turn it into a usable format.

4. Machine Learning- This will help to create predictable models from data. By mastering the basics of ML algorithms like linear regression, neural networks, decision trees, etc. it will be easier to understand how data science works.

5. Visualization of Data- Data Visualisation is very important to communication insights and information. Tools like Matplotlib (Python), Tableau and ggplot (R) will help in creating clear and proper visualisation works.

Online Courses and Certifications for Data Science

There are wide range of online courses available at Udemy, Coursera, and Upgrad for learning Data Science. The courses are offered by top data scientists, universities, and companies along with certifications which will help in impressing the interviewer to get a job as a Data scientist.

The courses from these platforms will help the user gain familiarity with tools like Jypyter Notebooks, Google Colab, Tableau, Google Cloud, AWS, Google Analytics, etc.

Qualification for becoming a Data Scientist

Data Scientists must have a bachelor’s degree in the field of computer science, statistics, maths, engineering, data science or related fields. Software developers with strong knowledge of data analysis tools like SQL, Python, R, SPSS, SAS, etc. help in coping with the complex problems of data science. 

Also, users coming from non-science or non-engineering backgrounds can take formal training in data analysis tools, make their base strong in maths and statistics can also start a career in Data Science.

How To Get a Job In the Data Science Field

To gain practical experience, internships are one of the best ways to start his/her career as a Data Analyst or Jr Data Scientist. After gaining significant skills and experience certifications, they can start applying for jobs in the data science community on LinkedIn or any other platform. Also, platforms like GitHub and Meetup.com are great for making connections related to the data science space. Also, a engineering or computer science graduate can bag a job in data science at their university placements. 

Conclusion

Starting a career in Data Science requires a strong commitment and understanding of programming languages, mathematics, machine learning, and in-hand experience. By going through the mentioned procedure one can easily get a job in Data Science or its related fields like Data Scientist, Data Analyst, Data Engineer, Data Architect, Machine Learning engineer, etc.

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