How To Start Your Career In Data Science

Introduction

In this new era of technology, there is data all over, and analyzing them has led us to better and smarter technologies in every field. With the ever-increasing load of data and the need to analyze them, it is time for an individual to build a career In data science. Data Science is one of the top 10 trending technologies in 2021 and has been providing visible career opportunities to several people.

Data science is the study dealing with the analysis of volumes of available data using scientific tools and mechanisms. Data Science includes acquiring data, preparation, mining & modeling, and maintenance of the model. Nowadays, data-driven jobs are on the rise, and it encourages various candidates to get started with data science.

Tips to start your Data Science Career

With the evolution of technology and the availability of data, companies nowadays look to certified data scientists to evaluate the provided data through modern tools and techniques and hand them an analysis that would help them in boosting the company’s performance.

Data science plays a crucial role in cyber security and fraud detection. Due to the analysis of a huge volume of data, the data scientists can find slight irregularities in the data that can be a threat to the security of the company. Data Science is responsible for highly specialized user experiences designed through personalization and customization.

According to Donald Farmer ‘Principal analytics consultancy’, TreeHive Strategy, Data Science undergoes six primary steps to analyze the data:

1. Identifying the business-related hypothesis to test.
2. Gathering the data to prepare it for analysis.
3. Analyzing the data with different analytical models.
4. Select the best model out of it and run the data against it.
5. Prepare a detailed report and submit it to the management board for evaluation.
6. Continue with the model for the other data as well.

Going forward with a career in data science is a good option with rising demands in several segments like banking, retail, government organizations, media, healthcare, transportations, and education.

8 Steps to Start a Career in Data Science

Let us look at some important steps on how to start a Career In Data Science. The freshers are not expected to display a high level of expertise, but with the right guidance, the candidates can provide invaluable analysis of the data to the company.

1. Understand what you need to learn

One needs to understand the details like the course duration, languages to be learnt, eligibility, etc. regarding data science before registering for the course. Discuss with the experts from Board Infinity to know all the courses required to be a successful data scientist.

Various modules, courses, languages, tools, and technologies to be learned to be an expert in data science. The candidates need to be expertise in the tools and languages linked with Data Science before getting started with Data Science. The industry experts can guide on what tools are more efficient to learn Data Science.

2. Learn Python and R

If you are looking to learn data science, learning Python and R is essential. R is more popular in academics, whereas Python is used more in industries. You need not learn both of them but have to perfect one of them to excel in data science. All the modern tools and technologies can be implemented with ease for a person well-equipped with the knowledge of Python and R.

The Python programming certification course from Board Infinity would introduce aspiring data scientists to the fundamentals of the language like data structures, networked application program interfaces, and databases.

3. Learn about Machine Learning, Modeling, Statistics, Programming, and Database

Machine learning, modeling, statistics, programming, and databases are the tools of data science. One should be properly equipped with the knowledge of machine learning, statistics, programming, and database to work on these tools. With the help of these tools, a data scientist can analyze the volumes of data and submit a detailed report to the company.

Machine learning is not easy and requires a high level of understanding and it evolves along with the rapidly evolving technologies. The candidate should invest proper time in learning ML while undergoing a data science course. This would help them in jumpstarting their professional career in data science. Companies are looking for candidates who can analyze their data with modern tools, and the candidates should work on it.

4. Focus on Practical Applications

During the training phase, the candidate should spend more time on implementing the theory learnt to gather more knowledge on data science instead of just reading theory. The more exposure to practical applications, the more would be the experience in handling volumes of data and analyzing it.

The best way to learn data science is to implement your knowledge of Data Science on practical applications. So, with practical applications, the candidates can understand the concepts more properly and would give them initial exposure to the real work environment. With learning alongside practical, the candidate can learn more efficiently and can prove as an excellent asset for the company.

5. Get Practical Exposure Through Internships

Every company is looking for experienced data scientists to work on their data. So, it is highly recommended to go through internships in various companies to get a hold on the job profile. The best way to learn data science is through practical application. It gives the candidate an edge over the others.

Many companies are looking for candidates for internships. With a certification course in data science from a recognized institute, the students can apply for these internships. This would give them a detailed exposure to the field and would prepare them for bigger roles in companies after they are hired.

6. Keep Updated with the Changing Industry Trends

The world of data science is changing dynamically. A candidate who is looking to build a career in data science should always stay updated with the latest trends in the tools and technologies. With the evolution of analysis of data, one needs to understand that data can be analyzed in several ways, and companies are looking for candidates who can give them more detailed information that can benefit their company.

With various courses like Big Data Hadoop & Spark, Business Intelligence using Power BI the candidates can stay updated with the latest trends and excel in their professional career. Staying updated with the latest trends can help a candidate to start their career in Data Science successfully.

7. Prepare a Professional Portfolio

Without a proper portfolio to reflect your experience and knowledge of data science, a candidate can never excel in their professional career. The candidates need to work on creating a well-detailed professional portfolio talking about the projects, the languages, tools, and techniques learnt by the candidate, and the experience through internships or jobs. This would help the company to select the right candidate for the role, and when you are selected for the right job, you can give your best and excel in your career.

After getting certified, creating a detailed portfolio is the basic step on how to start a career in Data Science. Your portfolio reflects your strength in Data Science and would help you in landing the perfect job. The professional portfolio is the first step towards the candidate being accepted or rejected. So, the candidate needs to spend a good amount of time and should take help from industry experts in framing the professional portfolio.

8. Get Certified

The Data Science Certification helps in mastering technologies like Python, SQL, along with Regression models, Data Exploration, and hypotheses. The certified data science course from Board Infinity is in line with the SSC NASSCOM and approved by the Government of India. It is ok to learn Data Science, but getting certified from a recognized institute gives you an extra edge over others.

Getting certified opens up a wide range of job opportunities for a candidate like Data Analyst, Data Scientist, Machine Learning Engineer, Data Storyteller, and many others. The candidate needs to choose the job opportunity as per the requirements and qualifications.

These are some of the tips on how to build a career in data science. The candidates need to understand the details of the course before thinking about how to learn data science. There are various modules, tools, and techniques involved with it, and the candidate needs to be strong in that to excel in their data science career.

Conclusion

The candidates looking to build a career in Data Science should understand the topics discussed above and should go through them to excel in their careers. From strengthening the foundation of data science to building a robust portfolio, to getting certified in data science, the candidates need to work hard on getting started with Data Science as their professional career.