What subjects are in data science?

The Data science subjects include Linear algebra, machine learning, Data mining, statistics, cloud computing, etc. Candidates can check the detailed list of subjects and syllabus in the article above.

Is data science an easy course?

The data science course is comparatively hard. A wide range of knowledge across different fields is necessary to master the skills required in data science. Data scientists require a diverse range of skills and knowledge, ranging from programming languages such as Python or R to SQL database queries and mathematical abilities such as calculus and linear algebra.

Is data science full of maths?

Although math is an essential part of data science, you don't require as much knowledge as you believe. Let's examine how experts utilize mathematics in data science and the level of mathematical knowledge required to enter this promising and profitable career path.

Data Science Course Syllabus 2025, Check Data Science Course Subjects -

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If you will look for the trendiest job of the 21st century, you will get the name of Data Science in that list. The Data Science is arguably the most in-demand course at the present time all over the world. But what special impact this field has that has led to its exponential rise and how does the Data Science course provide those trendiest skills that is the dream of every working professional to acquire in contemporary times. In this post, we will discuss about the Data Science Course Syllabus and the subjects that are taught in the Data Science course.

Data Science Course Syllabus

The syllabus of the Data Science course is filled with all the topics and subjects that are required to excel in the modern tech-driven world. The core topics in any data science course syllabus includes Statistics, Programming, Machine Learning, Artificial Intelligence, Mathematics, and Data Mining, regardless of how the course is taught. As you review the data science syllabus, you will encounter various procedures, techniques, formulas, and tools. Therefore, it is essential to carefully review the curriculum when selecting a data science course that aligns with your career ambitions and objectives!

Data Science Course Syllabus Overview

Data science is frequently seen as the most profitable career path of the twenty-first century, playing a crucial role in the operations and service delivery of organizations globally. Educational institutions are making efforts to meet the increasing demand for data scientists around the world.

A data science course is a unique program that aims to introduce you to concepts and processes in data science. It contains detailed information on statistical methods and tools for data analysis. You will also be taught how to handle statistical data or unprocessed data gathered from various sources. Below is a summary of the course syllabus for the data science class.

Particulars	Details
Name of the Course	Data Science Course
Course Duration	3 months to 3 years or more
Course Mode	Offline or Online
Eligibility Criteria	Students should have studied Mathematics at 10+2 or UG level, however, the requirement is relaxed for online courses
Prerequisites	Foundational knowledge of computer science, statistics, and mathematics will help
Data Science Course Key Subjects	Probability & Statistics Programming in Python R Programming MySQL Mathematics Data Analytics
Job Profiles Available	Data Analyst, Data Scientist, Data Engineer, Business Analyst, Project Manager, Business Strategist, etc.
Courses Available	BSc. in Data Science, BCA in Data Science, B. Tech in Data Science, MSc. in Data Science, and more.

What is Data Science?

Before knowing the Data Science syllabus, students should know what actually is Data Science. The study of data to derive valuable business insights is known as data science. It is a multidisciplinary method for analyzing vast volumes of data that blends ideas and methods from computer engineering, statistics, artificial intelligence, and mathematics. Questions like what happened, why it happened, what will happen, and what can be done with the results are all addressed by this approach.

Data Science Course Syllabus 2025

The Data Science course syllabus is dynamic and some of the technology subjects keep undergoing modifications. That is why, it is important for students to check the latest syllabus for the data science program. The contemporary learners should check the Data Science course syllabus 2025 given here.

Although the curriculum for data science is consistent among different degrees, there may be variations in the projects and elective courses. For example, the curriculum for a B.Tech. in Data Science includes practical labs, projects, and thesis work, unlike the B.Sc. in Data Science. Likewise, the M.Sc. in Data Science focuses on research-oriented education, with a focus on specific training and research projects.

Data Science Course Syllabus for Entry Level

Individuals who have finished their 10+2 education can register for beginner-level data science courses. Numerous platforms provide a data science course tailored for novices. The main components of the beginner’s data science curriculum are outlined in the table below:

Subject Name	Syllabus	Brief Detail
Introduction to Data Science	Introduction to data analysis tools Data structures Linear Regression Statistical Inference Statistical Models	The fundamentals of data science are covered in this subject.
Cloud Computing	Database Management Visualization Cloud Architecture Model Services Cloud Security	The basics related to cloud computing are covered in this subject.
Data Mining	Mining from different databases Preprocessing data Data Modelling Clustering Data Detecting Anomaly Multi-dimensional Modeling of Data Data Prediction and Classification Techniques	Various data mining techniques and tools are explored in this subject.
Data Visualization	Introduction to Data Visualization Acquiring and Visualizing Data Applications of Data Visualization Data Visualization tools and techniques	This subject provides hands-on knowledge and experience of using data visualization tools
Data Analysis	Probability and Statistics Business Fundamentals Customer Analytics Retail Analytics Social Network Analysis Pricing Analysis Statistics Introduction to BIS (Business Information Systems)	The fundamentals of data analysis, processing, and interpretation are covered in this subject.
Machine Learning	Linear Algebra Statistical Learning Scalable Learning Programming For Data Analysis Big Network Data Deep Learning Machine Learning Models Training Algorithms	The various prerequisites of machine learning and applications of machine learning are discussed in this subject.
Business Intelligence	Introduction to BI Learning objectives of BI Components of BIS (Business Information Systems) Business Intelligence and Analytics BI and Decision-Making	The fundamentals of BI and their applications in various aspects of business are to be studied in this subject. The students learn how to use BI techniques and insights to improve business decisions by going through the topics of this subject
Data Warehousing	Data Warehousing and Business Analysis Components of Data Warehousing How to build a data warehouse? Architectures for Data Warehousing Data Warehousing Design Business Intelligence using SAP Business Objects	The basics of data warehousing, data warehouse building techniques, and their applications are explained in this subject.
Data Dashboards and Storytelling	Creating Static Charts Interactive Dashboards and data stores Data Visualization Using Tableau Storytelling Techniques	The basic concepts and uses of charts, diagrams, and other graphic elements in data visualization are to be studied in this subject. It gives the students a basic idea of how to present data in a meaningful way.

Data Science Syllabus Course Wise

The Data Science program is offered by many authority in various forms. Some established colleges offered the course through bachelor’s or master’s degree while online platforms offer the course in the form of Diploma or certification. Students can check the latest Data Science syllabus for various programs in the following table:

Program Name	Eligibility Criteria	Important Topics
IIT Data Science Program (B. Tech in Data Science and Engineering)	Students must have studied Science with Physics, Chemistry, Mathematics and Computer Science (not mandatory) in 10+2The students must also qualify the entrance test for admission to this course.	Data Handling and Visualization Machine Learning Mathematical Foundations of Data Science Matrix Computations Stochastic Models Statistical Learning Information Security and Privacy Optimization Techniques Python Programming Lab Scientific Computing
BSc Data Science Course	10+2 in Science with Physics, Computer Science, and Mathematics. The college or university in which the students apply may or may not hold an entrance test.	Introduction to Data Science Data Visualisations Cloud Computing C Programming Language Machine Learning Basic Linear Algebra Optimization Techniques Big Data Analytics Probability Statistics Basics
B. Tech Data Science Program	10+2 in Science with Physics, Computer Science, and Mathematics. The students must also clear the entrance test to qualify for this course.	Algorithm Design and Analysis Engineering Physics Data Warehousing Database Management System Data Acquisition Introduction to Artificial Intelligence and Machine Learning Mathematics Object Oriented Programming (OOPs) Programming Python Statistics
MSc Data Science Course	The students who have completed their B. Tech or BSc. in Data Science can apply for this course. Entrance tests are usually not conducted but some colleges or universities may conduct their CET (Common Entrance Test) to select the eligible candidates.	Artificial Intelligence Applied Statistics Computational Mathematics Database Management Deep Learning Machine Learning Optimization Technologies Python and R Spatial Sciences Mathematics
Data Science Course by Online Platforms	Individuals who possess basic understanding of computers and mathematics are eligible to enroll in this course.	Machine Learning Deep Learning Prompt Engineering Implementations Data Engineering Data Exploration Plotly NumPy Seaborn Spyder Tensor Flow Hadoop Power BI Docker Flask Python MySQL Jupyter Matplotlib

Data Science Syllabus Subjects

Whether you choose an online course, a traditional classroom setting, or a full-time university degree, the data science course outline stays the same. Although the specific tasks in each class may differ, all data science programs need to cover the basic principles of data science, as outlined below:

Data Science Syllabus Subjects
Data Visualization	Machine Learning	Deep Learning
Data Mining	Programming Languages	Statistics
Cloud Computing	EDA	Artificial Intelligence
Big Data	Data Structures	NLP
Business Intelligence	Data Engineering	Data Warehousing
DB Management	Liner Algebra	Linear Regression
Spatial Sciences	Statistical Interference	Probability

The field of data science brings together mathematics, programming, machine learning, and domain expertise to harness the potential of data. It is crucial for individuals interested in a career in data science to excel in the fundamental subjects and stay informed about new developments. Having a solid grounding in the mentioned subjects allows up-and-coming professionals to effectively handle the intricacies of data science and take advantage of its increasing job prospects.