Essential Tips for A Data Scientist as A Fresher


Data science is a promising and increasingly expanding field of study since it provides numerous career chances. Another factor that has arisen in recent years is the need for industries to make decisions based on data and analysis. The first steps in this career path may be somewhat difficult for novice specialists but any job is always interesting at the beginning. This article is to help at least the fresher’s who are willing to get into the field of data science with more concentration towards the opportunities available in Chennai, a brief about what data science is all about, and tips on how to start off a great career. Also, we will demonstrate how 360DigiTMG has fulfilled its role in offering quality data science course in Chennai.

Demand for Data Science in Chennai

Chennai, for instance, a major IT destination in India has been experiencing a growing demand for professionals in the data science field. A progressive IT industry, strong education system, and the elevated number of multinational companies are perfect conditions for data science professionals. Finance, health care, retail, manufacturing and many other sectors have become more dependent on analytics leading to demand for data scientists.

Companies in the Chennai city are keen to develop the competency of business intelligence to remain competitive. This is so due to the fact that data can be very useful in understanding customers’ behaviours, market trends and improving various operations within an organisation. As a result, most of the focus is given to preparing the future workforce to fit the necessary skills in data science to work in the industry.

What is Data Science?

It is defined as an inter-disciplinary field that uses statistics, computing and business/subject specific knowledge to process data for producing valuable information. It encompasses data acquisition, pre-processing, processing, visualisation and post-processing. Data science is an applied field whose purpose is to reveal information hidden within large datasets for the purpose of decision-making and organizational efficacy.

1. Data Collection: 

Gathering data from various sources such as databases, APIs, and real-time sensors.

2. Data Cleaning: 

Preprocessing data to remove inconsistencies, errors, and duplicates.

3. Data Analysis: 

Using statistical methods and algorithms to explore and interpret data.

4. Machine Learning: 

Applying algorithms that enable computers to learn from data and make predictions or decisions.

5. Data Visualization: 

Creating visual representations of data to communicate findings effectively.

6. Data Engineering: 

Building and maintaining the infrastructure required for large-scale data processing.

Data science has applications across various industries, including healthcare for predicting patient outcomes, finance for detecting fraudulent transactions, and retail for optimizing supply chains.

Essential Tips for a Data Scientist as a Fresher

1. Maintain a Firm Grounding in Mathematics and Statistics

Knowledge from probability and statistics, an understanding of linear algebra, and some calculus is considered necessary. These concepts make the framework for many data science algorithms and techniques.

2. Learn Programming Languages

One requires to have a good working knowledge in languages such as Python and R. These languages are used extensively in data science for basic operations such as data wrangling up to applying deploys for algorithms such as machine learning models.

3. Make Strides in Data Operations and Manipulation

Libraries like Pandas, NumPy in case of Python and dplyr in R are one of the most important resources in data analysis. To efficiently manage and analyse data, get to know these libraries.

4. Master Data Visualization

 One very important aspect is the ability to present the insights derived from the data in the form of figures. Master packages like Matplotlib, Seaborn, and Tableau that enable you to design and present data-driven visuals that will grab the audience’s attention and help them understand more about your discoveries.

5. Understand Machine Learning Algorithms

explicate the knowledge of basic machine learning algorithms like regression, classification, clustering, and deep learning. Get used to use these algorithms implementing through with libraries like scikit-learn and TensorFlow.

6. Work on Real-World Projects

– Specific and concrete practical experience cannot be underplayed. That is why it is effective to practice on real-life projects and with such theories in mind. Compete on Kaggle, apply for internships, or contribute to open source initiatives to gather practical experience.

7. Develop Strong Problem-Solving Skills

Data science lies in addressing issues and not finding solutions to mathematical problems. Learn how to approach problems systematically from recognizing the problem statement up to the integration stage and result interpretation.

8. Consultants also need to be current to market trends and changes.

Data science is one of the fields that is currently experiencing rapid change. It is advised to read articles on industry blogs, cast research papers and attend conferences to be up to date with current trends and developments.

9. Build a Professional Network

Networking provides a chance to gain access to jobs or other cooperations. People should join data science related groups, go to meetings, and meet other people through social media tools such as linkedin.

10. Take advantage of Professional Development courses

One of the suggestions is that you can take data science courses offered by different universities and colleges. For instance, 360DigiTMG offers extensive training courses that help the employees understand data science right from the fundamental levels up to the complex ones. Many of these programs also address hands on projects, opportunities for mentoring, and career guidance.

In this case, 360DigiTMG is one of the leading educational institutions that aims to offer excellent data science programs that enable learners to succeed in the market. Their programs are an applied theory that requires students to work practically with real-life projects as well as cases.

Key features of 360DigiTMG’s data science courses include:

Industry-Relevant Curriculum: To achieve relevance in the market courses are developed in conjunction with key industry stakeholders.

Experienced Instructors: This is because we have trainers with industry experience who provide guidance and share their knowledge with the candidates.

Practical Exposure: A strong focus on practical application of knowledge in the process supported by projects, internships, and live cases.

 Certification: Finally, participants are awarded a universally acknowledged certificate that opens the doors to a successful career.

Career Support: Supplying aids in resume construction, interview simulations, as well as employment opportunities.

This is a list of topics that are addressed in the data science programs offered by 360DigiTMG: data preprocessing, probability and statistics, machine learning, neural networks, and big data tools. These courses can be beneficial for students that want to enter the field of data science and obtain a competitive advantage on other applicants for data science positions in their respective industries.


There is rising demand for data science talents, especially in technology poles such as Chennai. Since organisations have embraced the application of data in their strategic decisions, the demand for data scientists will also increase. It is therefore important that anyone who is interested in the field of data science must have a clear picture on what it entails and the tools that are necessary for the job. This article gives ten tips that every aspiring data scientist should follow, which could be a good starting point for them. Furthermore, it is worth mentioning that, accredited educational facilities like 360DigiTMG provides learners with a combination of theoretical concepts and hands-on training that prepares the learners to fit the marketplace needs. With the help of these tips, freshers need to focus on quality learning resources and should be able to achieve their career objectives and be useful in transforming their organizations and industries into data-driven work environments.

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