Data science has made technology even simpler and easier. With the advancement of data science machine learning It has become very simple too. The syllabus of Data Science is made up of three main components: Big Data, Machine Learning and Modeling in Data Science. Major Topics in Data Science Syllabus statistics, Coding, Business Intelligence, Data Structures, Mathematics, Machine Learning, Algorithms, among others. Read this blog till the end to know about Data Science Syllabus and Syllabus.
What is Data Science?
In simple words, data science is a study of data, which includes algorithms, principles of machine learning and various other tools. It is used to record, store and analyze data to obtain important and useful information. Data scientists extract and examine data from a wide range of sources such as log files, social media, sensors, customer transactions.
data science syllabus
Data Science course syllabus consists of three main components, i.e. in Data Science big data, Machine learning and modeling. Here is the Data Science Syllabus:
- Introduction to Data Science
- Mathematical & Statistical Skills
- machine learning
- coding
- algorithms used in machine learning
- Statistical Foundation for Data Science
- Data Structures & Algorithms
- scientific computing
- optimization technique
- data visualization
- matrix computation
- scholastic models
- Experimentation, Evaluation and Project Deployment Tools
- Predictive Analytics and Segmentation Using Clustering
- Applied Mathematics and Informatics
- Exploratory Data Analysis
- Business Acumen & Artificial Intelligence
Data Science Syllabus for Beginners
If you are a beginner in data science, there are various introductory courses available online that you can take to get started with the basics about this course. Here is the Data Science Syllabus for Beginners:
- Introduction to Data Science
- Understanding Exploratory Data Analysis
- machine learning
- Model Selection and Evolution
- data warehousing
- data mining
- data visualization
- cloud computing
- business intelligence
- Story telling with data
- communication and presentation
Components of Data Science Syllabus
The Data Science Syllabus is designed to help the students to gather knowledge in the field of business. Its components are as follows:
- big data
- machine learning
- Business Acumen & Artificial Intelligence
- modeling in data science
Process modeling in data science
data science subjects
If you are planning to take a course in Data Science, it is imperative for you to know what are some of the topics from the syllabus that will be essential for your learning experience and will be essential to enhance your understanding of the course. So, if you want to know what are the topics under Data Science then here is a list which makes it clear. Here are the Data Science Subjects:
- Introduction and Importance of Data Science
- statistics
- information visualization
- Data Mining, Data Structures, and Data Manipulation
- Algorithm use in machine learning
- Data Scientist Roles and Responsibilities
- Data Acquisition and Data Science Life Cycle
- Deploying recommended systems on real world data sets
- Experimentation, Evaluation and Project Deployment Tool
- Predictive Analytics and Segmentation Using Clustering
- Applied Mathematics and Informatics
- Working on Data Mining, Data Structures, and Data Manipulation
- Big Data Fundamentals and Hadoop Integration with R
Data Science Syllabus IIT
IIT India offers Data Science and Engineering together with mtech in data science B.Tech offer. Here are the main topics covered under the syllabus of B.Tech in Data Science and Engineering by IIT Mandi:
- Data Handling and Visualization
- Information Security and Privacy
- Statistical Foundation of Data Science
- Optimization for Data Science
- Mathematical Foundation of Data Science
- Introduction to Data Structures and Algorithms
- Matrix Computation for Data Science
- computing for data science
- Introduction to Statistical Learning
Here are the main topics covered by IIT Guwahati under MTech Data Science Syllabus:
- Statistical Foundation for Data Science
- Data Structures & Algorithms
- stochastic models
- machine learning
- scientific computing
- optimization technique
- matrix computation
- python programming lab
- machine learning lab
BSc Data Science Syllabus
BSc Data Science is a 3 year graduation course which introduces the students to the basic fundamental concepts of data algorithms, structures, python programming, statistical foundations, machine learning etc. Here are the BSc Data Science Syllabus and Topics:
- Probability and Inferential Statistics
- Discrete Mathematics
- Data Warehousing and Multidimensional Modeling
- Object Oriented Programming in Java Machine Learning
- Operation Research and Optimization Technique
- Introduction to Artificial Intelligence
- cloud computing
- machine learning
- operating systems
- Data Structures and Program Design in C
- Basic Statistics
B.Tech Data Science Syllabus
BTech Data Science is a 4-year undergraduate course that introduces you to the core components of Data Science such as Business Analytics, Data Analysis, Machine Learning, Algorithms. Here is the BTech Data Science Syllabus:
- Introduction to Artificial Intelligence and Machine Learning
- Principles of Electrical and Electronic Engineering
- CAD design
- engineering physics
- engineering chemistry
- Application Based Programming in Python
- Data Structures Using C
- Applied Statistical Analysis
- computer network
- software engineering and testing methodology
- data mining
- artifical Intelligence
Are coding needed in Data Science?
Yes, to establish a successful career in this field, you need to have good knowledge of programming languages like C, C++, Java, SQL, Python, etc. But why so? Coding/Programming languages help you identify, analyze and organize unstructured data in an efficient manner. Thus these languages are an integral part of the Data Science syllabus.
FAQs
The duration of data science courses can vary greatly depending on the level of competency. Courses for diploma degrees can be as long as 20 weeks and last for several years, if one can pursue established programs such as a bachelor’s degree or master’s in data science or a related field.
Knowledge of some fundamental concepts of maths like algebra, calculus and statistics may be necessary for data science but background in maths is not mandatory.
It is important for the prospective student to have knowledge of programming languages like C++, Java, Python as coding is an important aspect of data science.
Hopefully, you must have come to know about the topics given in the Data Science Syllabus. If you want to do any course in data science abroad Leverage Edu You can book a free 30-minute session by calling the experts on 1800 572 000.