What Should I Take After 12th To Become a Data Scientist?

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These days industries, across the board are seeking data scientists.. For a 12th grade student trying to plan their future the journey to becoming one can be overwhelming. Fear not! This guide is here to lead you through the subjects you should pursue after grade if you’re interested in a thrilling career, in data science.

Understand the Role of a Data Scientist

Before you start mapping out your journey it’s crucial to grasp the nature of a data scientists role. Data scientists leverage their programming prowess to uncover insights, from vast amounts of data. They excel at detecting patterns, in datasets and constructing models that can forecast trends.

Basically data scientists play a role, in transforming data into valuable insights that drive business strategies and decision making. They have skills acting as statisticians, programmers, analytics experts, effective communicators and even storytellers. Key skills you require are mathematics, statistics, programming, domain expertise and machine learning.

Importance of Mathematics

Mathematics forms the bedrock on which data science is built. Hence aptitude in math is absolutely essential to pursue this field. The math you learn in 11th and 12th grade like calculus, linear algebra and probability will lay the foundation.

In college, you will study more advanced statistical concepts like multivariate calculus, sampling theory, significance testing, regression and Bayesian statistics. These mathematical skills will assist you in working on predictive modeling and analysis during your data science career.

Data Analysis and Statistics

Statistics – The Heart of Data Science

While math is the foundation, statistics is the heart of data science. Statistical techniques allow you to summarize large volumes of data and determine underlying patterns. Statistical models empower you to forecast future observations based on past data.

From descriptive statistics to predictive analytics, statistical methods permeate through the data science lifecycle. Statistics is all about making sense of variability in observations and uncertainty in results drawn from data. So taking up statistics is pivotal to become a skilled data scientist.

Importance of Computer Science

With the digital data deluge, coding skills are imperative for data professionals today. Collecting, storing, accessing, processing and visualizing data requires proficiency in programming. Data scientists work with vast datasets and cannot rely solely on software tools.

Hence you need to pursue computer science courses like Python programming, SQL, data structures & algorithms, operating systems, and databases. These will equip you with computational thinking and coding abilities to tackle data science challenges. Learning a multipurpose language like Python early on is a wise move.

Pursue Relevant Domain Knowledge

While math, stats and coding form the nucleus, you need domain training relevant to the data science role. For example, you could take up economics, finance, healthcare, engineering, humanities or social sciences. The domain knowledge will give you the background to understand business objectives in that vertical.

This domain expertise will help you develop meaningful data experiments, ask right questions and build appropriate models for that industry. You will be able to understand nuances in the data better. Pursuing academics in a field aligned to your target data scientist role is advantageous.

Be an Avid Learner

Data science combines diverse disciplines like computer programming, applied math, statistics, communication, visualization and business strategy. There are new frameworks and tools being introduced constantly. So you need intellectual curiosity and a passion for continuous learning.

Besides what you study in college, read up industry research, practice new skills and work on personal projects to build your capabilities. Develop knowledge of machine learning algorithms and their real-world usage. Learn tools like Python, R, SQL, Tableau, Spark and Hadoop. Stay updated on trends in analytics and data management by reading publications. Being an avid lifelong learner will hold you in good stead.

SQL Database

Pursue Data Science Internships

A degree will give you theoretical and practical grounding. But real insight comes from hands-on experience on actual data challenges businesses face. Hence pursue internships during summer vacations or electives in leading companies you would like to work for later.

Internships provide a valuable window into a day in the life of a data scientist in a particular domain before you take up a full-time job. This experience also builds up key skills, expands your knowledge and enables you to apply classroom learning. Additionally, it gives exposure to data science workflows and tools used in industry like Python, Tableau, etc. that will benefit you in your future career.

Choose the Right Higher Education Options

The most pertinent decision after 12th grade is what academics to pursue in higher education for a data science career. Let’s discuss the key options worth considering and how they will prepare you.

BSc in Statistics/Applied Mathematics A 3 year bachelor’s degree in statistics or applied mathematics helps sharpen your math skills and build statistical thinking. You cover concepts like linear algebra, statistical inference, probability, survey sampling, data mining, econometrics, etc. This provides a base for a data science master’s degree subsequently.

BA Economics with Statistics Minor If interested in business analysis, a bachelor’s in economics with a statistics minor imparts understanding on financial markets, microeconomics, macroeconomics combined with statistical abilities. Math, stats and economics aid decision modeling during your data science journey.

B.Tech in Computer Science A 4 year computer science & engineering bachelor’s degree enables you to specialize in subjects like machine learning, data mining, artificial intelligence, algorithms, soft computing, and information security. This provides advanced technical training to extract insights from data efficiently.

Integrated MSc in Data Science Several universities have started offering 5 year integrated Master of Science programs in Data Science for 12th pass outs. These provide end-to-end coverage spanning statistics, programming, data engineering, visualization, communication, ethics, applied projects and internships. By graduating, you evolve into a full stack data science professional.

Data Analyst Job

Conclusion – Data Scientist

We have covered central aspects like role of math, statistics, coding, domain expertise, continuous learning and higher education choices crucial for aspiring data scientists. Plan your undergraduate subjects wisely based on the role you want to take up. Build strong technical skills coupled with good business perspective.

Get some experience through internships before applying for leadership data science positions in global corporations. Stay abreast of latest developments. With meticulous preparation, perseverance and passion, an exciting big data career is well within your reach. Data science lets you combine analytical skills with real world problem solving. So go ahead and pursue your data dreams without hesitation after 12th.

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