How to become a Data Scientist after 12th in India 

The field of Data Science has exploded in recent years, becoming one of the most sought-after career paths in India and globally. The ability to extract meaningful insights from vast amounts of data drives innovation and decision-making across industries. For students who have just completed their 12th standard in India and are fascinated by the power of data, embarking on a journey to become a Data Scientist is an exciting and promising prospect. This article will guide you through the necessary steps, educational paths, and skills required to achieve this goal. 

What should I study to become a Data Scientist after 12th? 

While there isn't a direct "Data Science" degree immediately after 12th grade, the foundational knowledge acquired during your undergraduate studies is crucial. Several degree options can provide a strong base for a future in Data Science. The most popular and recommended paths include: 

• Bachelor of Science (B.Sc.) in Statistics: This degree provides a deep understanding of statistical principles, probability, and data analysis techniques, which are fundamental to Data Science. 
• Bachelor of Science (B.Sc.) in Mathematics: A strong mathematical foundation is essential for understanding the algorithms and models used in Data Science. Topics like calculus, linear algebra, and discrete mathematics are highly relevant. 
• Bachelor of Science (B.Sc.) in Computer Science: This degree equips you with programming skills, data structures, and algorithms, which are vital for handling and processing large datasets. 
• Bachelor of Technology (B.Tech.) in Computer Science or related fields (e.g., Information Technology, Software Engineering): These engineering degrees also provide strong programming and computational skills, often with some exposure to data analysis concepts. 
• Bachelor of Science (B.Sc.) in Data Science/Analytics: Increasingly, some universities in India are offering specialized undergraduate degrees in Data Science or Data Analytics. These programs are specifically designed to cover the core concepts and tools of the field. 

Choosing the right undergraduate degree depends on your aptitude and interests. A strong foundation in either statistics, mathematics, or computer science will serve as an excellent stepping stone towards a career in Data Science.Amrita Online's MBA in AI & DS builds upon the  focusing on AI and data science for business leadership. This MBA program prepares graduates to excel in roles requiring both technical expertise and strategic business acumen. 

What is the Eligibility for a Data Scientist? 

The eligibility criteria for becoming a Data Scientist typically vary depending on the specific role and the hiring organization. However, the following are common requirements: 

Educational Qualification: A bachelor's or master's degree in a quantitative field is usually required. Common fields include: 

• Statistics 
• Mathematics 
• Computer Science 
• Economics 
• Engineering (especially Computer Science, Electrical, or Industrial Engineering) 
• Data Science/Analytics 

  A Master's degree often provides a competitive edge and is sometimes a prerequisite for more advanced Data Scientist roles. 

• Technical Skills: Proficiency in programming languages like Python and R is often essential. Knowledge of database management systems (SQL, NoSQL), data visualization tools (Tableau, Power BI, Matplotlib, Seaborn), and machine learning libraries (scikit-learn, TensorFlow, PyTorch) is also crucial. 
   
• Analytical and Problem-Solving Skills: The ability to analyze complex datasets, identify patterns, and derive actionable insights is fundamental. Strong logical reasoning and problem-solving abilities are highly valued. 
   
• Communication Skills: Data Scientists need to effectively communicate their findings and insights to both technical and non-technical audiences through reports, presentations, and visualizations. 
   

Which Stream is Best for Data scientist after 12th? 

After completing 12th standard, the specific stream you choose (Science, Commerce, or Arts) can influence the ease with which you transition into a Data Science career. Generally, the Science stream with Mathematics is considered the most advantageous for aspiring Data Scientists. 

• Science with Mathematics: This stream provides a strong foundation in mathematics and statistics, which are core to understanding data analysis and machine learning algorithms. It also typically includes physics and chemistry, which can develop analytical and problem-solving skills. 
• Commerce with Mathematics/Statistics: Commerce students who have opted for mathematics or statistics as subjects also have a good foundation for pursuing Data Science. Economics, often a subject in Commerce, also introduces statistical and analytical concepts. 
• Arts with Mathematics/Statistics/Economics: While less direct, Arts students with a strong background in mathematics, statistics, or economics can also pursue a career in Data Science, especially if they complement their undergraduate studies with relevant technical skills like programming. 

Ultimately, regardless of the stream in 12th, a strong undergraduate degree in a quantitative field and the acquisition of necessary technical skills are the most critical factors in becoming a Data Scientist. 

Data Scientist Career Overview 

A Data Scientist is a professional who uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from noisy, structured, and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains. Their responsibilities typically include: 

• Data Collection and Preprocessing: Gathering data from various sources and cleaning, transforming, and preparing it for analysis. 
• Exploratory Data Analysis (EDA): Investigating and summarizing datasets to identify patterns, anomalies, and trends. 
• Feature Engineering: Creating new relevant features from existing data to improve the performance of machine learning models. 
• Model Building and Evaluation: Developing and implementing machine learning models to solve specific business problems (e.g., prediction, classification, clustering). Evaluating the performance of these models and fine-tuning them. 
• Data Visualization and Communication: Presenting findings and insights in a clear and understandable manner using charts, graphs, and dashboards. Communicating effectively with stakeholders. 
• Deployment and Monitoring: Deploying models into production environments and monitoring their performance over time. 
• Staying Updated: Keeping abreast of the latest advancements in data science, machine learning, and related technologies. 

The demand for Data Scientists is high across various industries, including technology, finance, healthcare, e-commerce, and consulting. This demand translates into attractive salary packages.Amrita Online strategically incorporates data science into its BCA (with AI and Data Science specialization), MCA (with AI and Data Science specialization), and MBA (in Business Analytics) programs. These programs aim to equip students with foundational to advanced data analysis and machine learning skills, tailored for technical or business-focused career paths in the data-driven landscape. 

Skills Required to Become a Data Scientist 

To excel as a Data Scientist, a combination of technical and soft skills is essential: 

Technical Skills: 

• Programming Languages: Proficiency in Python and/or R is crucial. 
• Statistical Analysis: A strong understanding of statistical concepts, hypothesis testing, regression analysis, and time series analysis. 
• Machine Learning: Knowledge of various machine learning algorithms (e.g., linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks) and their applications. 
• Deep Learning (Optional but increasingly important): Understanding of neural network architectures and deep learning frameworks like TensorFlow and PyTorch. 
• Big Data Technologies (Beneficial for large datasets): Familiarity with tools like Hadoop, Spark, and cloud computing platforms (AWS, Azure, GCP). 
• Database Management (SQL and NoSQL): Ability to query and manage data from relational and non-relational databases. 
• Data Visualization: Proficiency in tools like Tableau, Power BI, Matplotlib, and Seaborn to create insightful visualizations. 
• Data Wrangling and Preprocessing: Skills in cleaning, transforming, and preparing data for analysis. 

Soft Skills: 

• Analytical and Problem-Solving Skills: The ability to think critically and solve complex problems using data-driven approaches. 
• Communication Skills: Excellent written and verbal communication skills to explain technical concepts to non-technical audiences. 
• Business Acumen: Understanding the business context and how data science can drive business value. 
• Curiosity and Continuous Learning: A passion for learning and staying updated with the rapidly evolving field of data science. 
• Teamwork and Collaboration: Ability to work effectively in a team environment. 

Steps to Become A Data Scientist 

Here’s a structured approach to becoming a Data Scientist after your 12th standard in Indi 

1. Choose the Right Undergraduate Degree: Enroll in a bachelor's degree program that provides a strong foundation in quantitative skills, such as B.Sc. in Statistics, Mathematics, Computer Science, or a specialized B.Sc. in Data Science/Analytics. A B.Tech. in Computer Science or related fields is also a good option. 
   
2. Focus on Core Subjects: During your undergraduate studies, pay close attention to subjects like statistics, probability, calculus, linear algebra, programming (especially Python and/or R), data structures, and algorithms. 
    
3. Gain Programming Proficiency: Develop strong programming skills in Python and/or R. Practice coding regularly and work on small projects to apply your knowledge. 
    
4. Learn Statistical Concepts: Build a solid understanding of statistical inference, hypothesis testing, regression analysis, and other fundamental statistical techniques. 
    
5. Explore Machine Learning: Once you have a good grasp of programming and statistics, start learning about machine learning algorithms and their applications. Utilize online courses, textbooks, and tutorials. 
    
6. Master Data Visualization Tools: Learn to use data visualization tools like Tableau, Power BI, Matplotlib, and Seaborn to effectively communicate insights from data. 
    
7. Work with Databases: Gain familiarity with SQL and NoSQL databases to store, retrieve, and manage data. 
    
8. Build a Portfolio: Work on personal data science projects to showcase your skills to potential employers. Participate in hackathons and contribute to open-source projects. Your portfolio should demonstrate your ability to solve real-world problems using data science techniques. 
    
9. Consider a Master's Degree (Optional but Recommended): A Master's degree in Data Science, Analytics, Statistics, Computer Science, or a related field can provide more in-depth knowledge and enhance your career prospects. 
    
10. Gain Practical Experience: Look for internships or entry-level positions as Data Analysts or Junior Data Scientists to gain real-world experience. 
     
11. Network: Attend industry events, connect with data science professionals on LinkedIn, and engage with the data science community. 
     
12. Stay Updated: The field of data science is constantly evolving. Continuously learn new technologies, tools, and techniques through online courses, certifications, and research papers. 

Becoming a Data Scientist after 12th in India requires a focused and dedicated approach. By choosing the right educational path, acquiring the necessary skills, and building a strong portfolio, you can successfully navigate this exciting and rewarding career path. Remember that continuous learning and adaptation are key to thriving in the dynamic field of Data Science. 

Frequently Asked Questions (FAQs) 

 How to become data scientist after 12th commerce?   

Choose a quantitative degree (B.Sc. Stats, Math, Econ, BCA), learn programming (Python, R), build skills, consider a Master's. 

 How to become data scientist after 12th PCB?   

Opt for a quantitative degree (B.Sc. Stats, Bioinformatics), strengthen math, learn programming, build relevant projects, consider a Master's. 

 Can a 12th pass get a job as a data analyst?   

Highly unlikely; a bachelor's degree is usually required. 

 How to become data scientist after 12th biology?   

Choose a quantitative degree (B.Sc. Stats, Bioinformatics), focus on math, learn programming, build biological data projects, consider a Master's. 

 What is the salary of data scientist after 12th?   

No typical salary, as a degree is needed for such roles. 

 What is the entrance exam for data science after 12th?   

No specific exam; focus on entrance exams for relevant undergraduate degrees (e.g., CUET, university-specific tests, engineering exams for B.Tech). 

Conclusion 

In conclusion, while the path to becoming a Data Scientist after the 12th standard in India isn't a direct one, it's certainly achievable with careful planning and dedication. Regardless of your chosen stream in 12th, the key lies in pursuing a relevant undergraduate degree that builds a strong foundation in quantitative skills like mathematics and statistics, coupled with acquiring proficiency in programming and data analysis techniques. Building a strong portfolio through projects and considering a Master's degree can further enhance your prospects in this dynamic and in-demand field.  

You May Also Like 

• Difference Between UG and PG- Top Courses, Salary   
• UP Scholarship  2024-2025: How to Apply—Pre-Matric and Post Matric Scheme  
• Digital Gujarat Scholarship: Overview, Status, and Last Date 
• How to apply online for PM Yashasvi scholarship—Eligibility and Syllabus 
• DCE Scholarship: Eligibility Criteria, Application, Required Documents, Scholarship Rewards, Last Date  
• MPTAAS Scholarship: All You Need To Know