Data Science Syllabus and Subjects 2024

Data science syllabus and subjects teach students how to work with data using various tools and software. Before choosing a college or university to enroll in, it's important to check the semester-wise data science syllabus. 

The core data science subjects include Statistics, Programming, Machine Learning, Artificial Intelligence, Mathematics, and Data Mining. These subjects are taught in almost every Data Science course, regardless of whether it's online, classroom-based, or a full-time degree.

The data science 1st year syllabus consists of Linear Algebra, Basic Statistics, Programming in C, Communication Skills in English, and Fundamentals of Data Science. Although the basic syllabus is the same for different data science degrees, projects, and electives may differ. For example, the BTech Data Science course syllabus includes labs, projects, and dissertations, while the MSc Data Science course focuses more on research-oriented topics, training, and research projects.

Data Science syllabus facts - 

• The duration of the data science course may vary. The duration range is 3 to 4 years for undergraduate degrees, 2 years for Post Graduate, and Post Graduate Diploma courses.
• For Data Science Admission 2024, candidates have to be 10+2 qualified candidates in the Science stream with at least 50% marks to get admission to UG courses. While the data science eligibility criteria for PG and PG diploma courses are candidates are required to have completed their bachelor’s degree in a relevant discipline with 60% marks. 
• The data science job profiles offered after the completion of the course are Data Scientist, Data Analyst, Applications Architect, Machine Learning Scientist, and Enterprise Architect.
• Some of the major recruiters of data science are Amazon, Flipkart, Cognizant, Wipro, HCL, and Dell.
• Following are the data science course fees for several degrees - B.Sc Data Science is INR 50,000 to INR 1,00,000, BTech Data Science is INR 1,80,000, M.Sc Data Science is INR 20,000 to INR 70,000, M.Tech Data Science is INR 50,000 to INR 2,00,000 and Post Graduate Diploma in Data Science is INR 30,000 to INR 5,00,000.

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Candidates can check the data science subject highlights have been listed in the table below.

Data Science Syllabus is designed to make sure that students can fully learn about data science, business, and business studies. The Data Science syllabus is devised keeping the needs of the industry in mind. The Data Science program offers a wide range of subjects. Given below is the Semester Wise Data Science subjects -

Data Science 1st Year Syllabus 

The table given below contains the Data Science 1st Year subjects which have been divided semester wise here-

Data Science 2nd Year Syllabus 

The semester wise Data Science subjects for the second year are given below -

Data Science 3rd Year Syllabus 

The semester wise Data Science subjects for the third year are given below -

Various institutes provide different programs and streams for Data Science course specialization. The following are some of the prominent Stream Wise Data Science Syllabus.

IIT Data Science Course Subjects

The following major Data Science subjects at the IIT are -

• Information Security and Privacy
• Mathematical Foundations of Data Science
• Stochastic Models
• Machine Learning
• Scientific Computing
• Optimization Techniques
• Matrix Computations
• Python Programming Lab
• Statistical Learning 

BSc Data Science Course Subjects

The Bachelor of Science (B.Sc) program is three years long and divided into six semesters. The following is the B. Sc Data Science syllabus:

• Introduction to Data Science
• Statistics Basics
• Linear Algebra
• C Programming Language
• Probability
• Cloud Computing
• Machine Learning Basic
• Optimization Techniques
• Big Data Analytics 
• Data Visualizations 

BTech Data Science Program

The Bachelor of Technology (B.Tech) program at the undergraduate level lasts 4/3 years (8/6 semesters). The following is a course syllabus for the BTech in Data Science:

• Mathematics 
• Programming
• Engineering Physics
• Introduction to AI and ML
• Python
• Statistics 
• Object Oriented Programming (OOP)
• Data Acquisition
• Database Management System
• Data Warehousing
• Algorithm Design and Analysis 

MSc Data Science Program

The Master of Science (MSc) program is a two-year postgraduate course (4 semesters). The semester-wise syllabus for the MSc Data Science is as follows:

• Applied Statistics
• Spatial Sciences Mathematics
• Python and R
• Database Management
• Computational Mathematics
• Optimization Technologies
• Deep Learning
• Machine Learning 
• Artificial Intelligence 

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Data Scientist candidates will have hips of responsibilities as it forms the base of a company where they are the ones to make the important decisions by analyzing the past and future possibilities. The essential competencies and skills that every employer looks for in a candidate are the crucial data science subjects listed below.

• Business Intelligence: Candidates will be in charge of constructing decisions at different designations, so they should be acquainted with the most recent BI tools.
• Probability and Statistics: The most compulsory aspect of data science is established on mathematical fundamentals such as probability, statistics, and linear algebra. 
• Machine Learning: Some of the main ML algorithms candidates should focus on are degeneration approaches, the Naive Bayes algorithm, and regression trees. 
• Programming Languages: The most efficient and mighty programming languages for data science are thought to be Python and R.
• Data Manipulation: When it comes to comprehending data sets, data manipulation and data visualization evolve as essential subjects.

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The data science subjects are usually the same whether they are in online, or offline mode. Some of the best topics covered in data science are listed below - 

The data science course syllabus is designed to ensure that students have access to all the essential information they require. The course is flexible and diversified because it is separated into core and elective areas.

The following is the data science syllabus, along with the majand or topics that students must learn about-

As industries are moving towards advancements, they are using big data and machine learning for their business growth, and the demand for data science professionals continues to reach its zenith. Candidates pursuing this course have to study and gain knowledge on various subjects. Some of the common subjects for all semesters are listed below. 

• Machine Learning
• Big Data
• Statistics

If you're interested in data science but don't know where to start, you can take beginner courses online. Websites like Udemy, Coursera, Google, Microsoft, and IBM offer a wide range of data science courses for beginners. Some of the topics covered in these courses include data analysis, data visualization, machine learning, and business intelligence. If you're curious about what a beginner's data science course syllabus might look like, check out the list below:

- Cloud Computing

- Introduction to Data Science

- Data Mining

- Data Visualization

- Data Analysis

- Machine Learning

- Data Model Selection and Evaluation

- Data Warehousing

- Business Intelligence

- Data Dashboards and Storytelling

Below is a list of optional semester wise Data Science subjects that are offered to students to help them gain expertise in a particular subject: 

• Reinforcement Learning
• Marketing and Retail Analytics
• Supply Chain and Logistics Analytics
• Financial Analytics
• HR Analytics
• Social Media Analytics
• Healthcare Analytics
• Nature Processing Analytics
• Software Quality Management
• Software Testing
• Econometrics
• E-Commerce
• Tensorflow for Deep Learning Research
• Visualization Techniques- TABLEAU

Given below is the list of Data Science Lab subjects-

• Programming in C Lab
• Microsoft Excel Lab
• Data Structure Lab
• Programming in R Lab
• Programming in Python Lab

Specializations in data science courses are commonly known as “tracks” or “focus areas”. Some of the Data Science Subjects Specializations are Statistics, AI, Deep Learning, and related. Let us go through each specialization one by one to have a better understanding.

Statistics

When first starting in data science or data analytics, it is important to understand statistical methods and techniques that will allow you to use data insights and transform them into usable results. Additionally, the importance of statistics is greatly expanding in this era of data-driven decision-making. Additionally, taking an online course in data science will teach data scientists how to use various statistical tools and methods to extract valuable information from raw, unstructured, and structured data.

Learning statistics would also enable students to use data and its applications across industries creatively and critically. The greatest online statistics courses with a focus on data science are available from numerous reputable Indian and international institutions. A few of the subjects covered in the syllabus are listed below:

• Hypothesis testing
• Bayes Theorem
• Random variables
• Mean, variance, standard deviation
• Linear regression

Python

Python is a computer programming language mostly used for creating websites and applications. Interestingly, due to its straightforward syntax and usability, it is a widely utilized programming language across many departments. Additionally, many colleges and institutions have specialist data science courses that introduce aspiring data scientists to the fundamentals of programming languages.

Artificial Intelligence

Artificial intelligence, in its most basic form, is a modern technology that uses machines to mimic actions taken by the human brain. Artificial intelligence subfields like machine learning and deep learning have made headway in numerous fields.

In the present era, when established enterprises are adapting, the market is changing, and the use of AI applications has increased, experts define artificial intelligence as the special fusion of science and engineering to produce smart and intelligent machines.

As a result, numerous institutions and colleges in India and abroad have created in-depth data science curricula that emphasize teaching students the principles of artificial intelligence.

Deep Learning

Deep learning is a type of machine learning that aims to imitate the actions of the human brain. Deep learning applications, in contrast to machine learning and artificial intelligence, fall short of the sophistication and wit of the human brain. However contemporary technology uses massive amounts of data to continuously learn and improve.

Deep learning powers many applications of artificial intelligence by improving automation and carrying out physical tasks automatically. Data scientists need to have a solid understanding of the various deep learning foundations and how to apply them to the process of data extraction, cleaning, and segregation. 

Machine Learning

Machine learning is a subfield of computer science and artificial intelligence that employs data to mimic how humans learn. It is used in numerous artificial intelligence applications to effectively operate machines without human input. Additionally, it offers a framework for machines to use the data to learn and update themselves.

Learning about the principles of contemporary technology can be aided by taking a machine learning course. Additionally, it gives the data scientist the ability to create, store, and analyze data efficiently so that robots may learn from it and keep themselves up to date. Additionally, specializing in the data science course syllabus above will help you acquire prospects and develop a successful career in the quickly changing field.

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The Data Science 1st year Syllabus along with the 2nd year for distance programs is similar to the regular courses. The detailed semester wise Data Science subjects Distance Programs are given below-

Coding is a fundamental skill in Computer Science, and Data Scientists ought to have a rudimentary knowledge of programming or coding. Data Scientists utilize programming languages such as Python, SQL, and R to pull, analyze and manage extensive datasets. Data Scientists also use programming to use Machine Learning models for Data Visualization and predictive critique. 

The way the Data Science syllabus and subjects are structured was intended to guarantee that the students have access to all the resources they require to complete the course successfully. The program includes both compulsory subjects and electives. The course outline is provided below:

• 6 Semesters
• Undergraduate Course
• Core Subjects
• Elective Subjects
• Research Project

The semester wise data science syllabus goes beyond simply knowing what kinds of data are available. If you wish to be a data scientist, you are required to comprehend a few other things. The other difficult and crucial modules in data science can be evaluated as - 

• Data Engineering
• Database management
• Big data engineering
• Machine learning or cognitive computing
• Data mining
• Data Analytics
• Predictive analytics

Data science books can be used to reference some theoretical principles and learn about data science applications. Given in the table below is the list of Data Science Important Books along with the author’s name