A Data science course teaches students how to work with structured or unstructured data using various tools, algorithms, and software. Students should be aware of the data science syllabus before deciding on a college or university to enroll in.
The basic Data Science syllabus is also the same for different Data Science degrees, but the projects and electives differ in such cases. For example, compared to the BSc Data Science course syllabus, the BTech Data Science course syllabus also includes labs, projects, and dissertations. Similarly, students focus on research-oriented topics, training, and research projects in the MSc Data Science course.
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2.2 BTech Artificial Intelligence and Data Science Syllabus
Data Science Course Syllabus
Data Science is one of the fastest-growing fields in the IT sector. Data Science finds applications in almost all fields including healthcare and finance. The trends in Data Science or the Data Science topics a student should pay attention to are as follows:
- Artificial Intelligence
- Auto Machine Learning
- Natural Language Processing (NLP)
- Data Fabric
- Cloud Migration
- Data as a Service
- Robotic Process Automation (RPA)
- Federated Learning
- Data Democratisation
- Data Regulation and Governance
Data Science Syllabus: Course-Wise
BSc Data Science, MSc Data Science, BTech Data Science, MTech Data Science, etc. are top Data Science Courses After 12th. The sections below discuss the data science course syllabus of these top data science courses after the 12th in detail.
BSc Data Science Syllabus
BSc Data Science syllabus is divided into 6 semesters. The syllabus for each semester is different and includes Artificial Intelligence, Applied Statistics, and Cloud Computing, along with elective subjects. The main BSc data science subjects are mentioned in the table below. To check the complete syllabus, download the BSc Data Science Syllabus PDF.
| Linear Algebra | Probability and Inferential Statistics |
| Basic Statistics | Discrete Mathematics |
| Programming in C | Data Structures and Program Design in C |
| Object-Oriented Programming in Java | Machine Learning |
| Database Management Systems | Cloud Computing |
| Big Data Analytics | Data Visualizations |
BTech Artificial Intelligence and Data Science Syllabus
The main topics covered in the BTech artificial intelligence and data science course are mentioned in the table. To check the complete syllabus, download the BTech Artificial Intelligence and Data Science Syllabus PDF.
| Calculus | Engineering Physics |
| Engineering Chemistry | Python Programming |
| Data Structures | Data Science and Analysis |
| Computer Networks | Machine Learning |
| Deep Learning | Embedded Systems |
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BTech Data Science Syllabus
BTech Data Science is a 4 year undergraduate course with an 8-semester system and 6 program electives. The main topics covered in the BTech data science course are mentioned in the table. To check the complete syllabus, download the BTech Data Science Syllabus PDF.
| Introduction to Artificial Intelligence and Machine Learning | Application-based Programming in Python |
| Maths | Advanced Physics |
| Engineering Physics | Engineering Chemistry |
| Discrete Structures | Data Acquisition |
| OOPS using Java | Principles of Operating System |
| Data Structures using C | Database Management System |
| Design and Analysis of the Algorithm | Artificial Intelligence |
Quick Links:
| Data Science Courses After 12th | Data Science Certification |
| Google Data Scientist Certification | IBM Data Science Professional Certificate |
BCA Data Science Syllabus
BCA Data Science is a 3 years undergraduate course having 6 semesters. The course curriculum is designed to teach advanced in-depth knowledge of Data Science and software applications. The main topics covered in the BCA data science course are mentioned in the table. To check the complete syllabus, download the BCA Data Science Syllabus PDF.
| Discrete Mathematics | Statistics and Probability |
| Environmental Science and Sustainability | Database Management System |
| Computer Essentials for Data Science | Data Structure and Algorithm |
| Computational Thinking and Programming in C | Operating System |
| Object-Oriented Programming using C++ | Introduction to Java and Web Programming |
| Software Engineering | Python Programming Lab |
| Data Modelling and Visualization | Big Data Analytics |
| R Programming for Data Sciences | Information and Data Security |
| Machine Learning | Natural Language Processing |
MSc Data Science Course Syllabus
MSc Data Science is a 2 year postgraduate program. The course revolves around Calculus, Descriptive Statistics, C Programming, and the use of various technologies such as ML, DL, Python, and Spark. The main topics covered in the MSc data science course are mentioned in the table. To check the complete syllabus, download the MSc Data Science Syllabus PDF.
| Mathematics for Spatial Sciences | Spatial Big Data and Storage Analytics |
| Applied Statistics | Data Mining and Algorithms |
| Fundamentals of Data Science | Machine learning |
| Python Programming | Advanced Python Programming for Spatial Analytics |
| Introduction to Geospatial Technology | Image Analytics |
Data Science Syllabus for Beginners
Data science beginners or those who want to check out data science courses after class 12th can pursue data science courses online. There are plenty of data science courses for beginners online by Udemy, Coursera, Google, Microsoft, and IBM. Check out the data science course syllabus for beginners in the section below:
- Introduction to Data Science
- Data Mining
- Cloud Computing
- Data Analysis
- Data Visualization
- Data Model Selection and Evaluation
- Machine Learning
- Business Intelligence
- Data Warehousing
- Data Dashboards and Storytelling
Is Coding Required in Data Science?
Yes, coding is needed in Data Science. Data Scientists use programming languages such as Python, SQL, and R to extract, analyze and manipulate large datasets. They also use programming to use Machine Learning models for Data Visualization and predictive analysis. Coding is a fundamental skill in Computer Science, and Data Scientists need to have a fundamental knowledge of programming or coding.
Top Data Science Books
Practical Statistics for Data Scientists by Andrew Bruce and Python Data Science Handbook by Jacob T. Vanderplas are the top 2 data science books recommended for aspiring data scientists. The table lists the best data science books for beginners as well as professionals in the field of data science.
| Book Name | Author |
|---|---|
| Python Data Science Handbook | Jake VanderPlas |
| Practical Statistics for Data Scientists | Peter Bruce, Andrew Bruce & Peter Gedeck |
| Introducing Data Science | Davy Cielen, Anro DB Meysman, Mohamed Ali |
| The Art of Statistics Learning from Data | David Spiegelhalter |
| Data Science from Scratch | Joel Grus |
| R for Data Science | Hadley Wickham & Garrett Grolemund |
| Think Stats | Allen B Downey |
| Introduction to Machine Learning with Python | Andreas C Muller & Sarah Guido |
| Data Science Job: How to Become a Data Scientist | Przemek Chojecki |
| Hands-on Machine Learning with Scikit-Learn and TensorFlow | Aurelien Geron |
Data Science Course Syllabus: FAQs
Ques. Should I learn R or Python if I want to become a data scientist?
Ans. Both programming languages are useful in Data Science. While Python is a general-purpose programming language, R is a platform for statistical analysis. R should be used for computational statistics and machine learning whereas Python should be used for programming and building applications.
Ques. What subjects should I choose if I want to become a data scientist?
Ans. Statistics and Computer Science are the top majors for an aspiring Data Scientist. A degree in Statistics would focus on the applications of Data Science as well as Data Analysis. A degree in Computer Science will help in understanding Machine Learning in the future.
Ques. What are the core data science subjects?
Ans. The basic Data Science subjects are Python, R, Statistics, and Data Engineering.
Ques. What level of math is required for data science?
Ans. Linear Algebra, Statistics, Calculus, Discrete Maths, and Probability are the mathematical concepts that are included in Data Science.
Ques. Can I study data science online?
Ans. Yes, there are different kinds of data science courses available online, ranging from certificate, diploma and even degree levels. Udemy, Coursera and Simplilearn are the top platforms known for the best data science courses online.
Ques. What are the main BSc data science subjects?
Ans. The main BSc data science subjects are Artificial Intelligence, Applied Statistics, and Cloud Computing.
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