In the world of digitalisation and the internet, data is everything. More and more data gets accumulated as and when some online activity occurs. As per the reports, around 1.7 MB of data gets generated every second for every person. This data is beneficial for companies in determining growth trends and customer purchasing behaviour. But it is difficult to handle such a massive amount of data, so they have started hiring for Data Science roles. As the amount of data is increasing, so is the demand for Data Scientists. Let us learn about the field, its syllabus, subjects, and course fees. Before that, let us understand data science and the roles and responsibilities of a data scientist.
What is Data Science?
Data Science refers to the field of study that deals with enormous volumes of data and uses modern tools, techniques, processes, and algorithms to find unseen patterns, extract knowledge, and reach conclusive knowledge that can be applied to solve a broad range of problems.
It is a new field in science and technology and has gained popularity in recent years globally. Everything we do generates some data, whether website data or personal data. With the internet of things in use, Data Mining and Big Data are being used more intensively. Companies have started investing more in Big Data, which controls how people act or think.
Data Science has widely impacted almost every sector. Several opportunities have been created by the applications of Data Science in the areas such as education, science, healthcare, sports, security, and energy. All Data Science based studies depend upon the datasets measuring and analysing scientific goals. The number of opportunities created in the Data Science field with a handsome salary offered by the area has attracted IT enthusiasts. If you also want to make a career in Data Science and looking for the Data Science course fees, subjects, and syllabus, this article is for you. Read further to know all the details.
Activities performed by Data Scientist
A Data Scientist has to perform several activities as described below:
- Work with their professional superiors to identify the business challenges they want to solve and use data to provide insights, thus helping them in better decision-making.
- Create algorithms to manage, merge, interrogate, and extract data to create customised reports for colleagues and customers.
- Use Machine Learning related tools and other statistical techniques to produce solutions to the problems.
- Use Test Mining models and choose the most suited for the project.
- Have coherent and clear communication to make others understand the data requirements and reports generated.
- Design reports that tell a compelling story of how clients and business work.
- Assess the effectiveness of data sourcing and find ways to improve the data collection.
- Stay up to date with the latest technologies and practices in the field of data science.
- Perform research that helps develop proofs of concept and prototypes.
- Find opportunities using the datasets and insights across different functions in the company.
- Stay enthusiastic about using various algorithms and find innovative solutions to the problem statements.
Data Science Subject Syllabus
The subjects in Data Science engineering remain more or less the same, whether you opt for an online or offline course. The projects may vary, but the core concepts are mandatory for the system. In this section, know the Data Science subject syllabus for beginner, graduate and master levels. You can download the Data Science course syllabus PDF from the institution's official website where you apply. Newton School also offers a Master's in Data Science dual degree from IU University, Germany, and London South Bank University, England.
Data Science Course Syllabus for Beginners
If you are new to the Data Science field, you need to get familiarised with the introductory courses with basics. Check the Data Science course syllabus for beginners as below:
- Introduction to Data Science
- Exploratory Data Analysis
- Data Visualization
- Machine Learning
- Model selection and evaluation
- Data Mining
- Data Warehousing
- Cloud Computing
- Business Intelligence
- Communication and Presentation
- Storytelling with Data
B.Sc. in Data Science Syllabus
Below are the semester-wise Data science Subject Syllabus:
Semester 1:
- Introduction to Data Science
- Statistics
- Linear Algebra
- C Language
- Microsoft Excel
Semester 2:
- Discrete Mathematics
- Probability
- Inferential Statistics
- Data Structures
- R Programming Language
- Data Warehousing
- Multidimensional Model
Semester 3:
- Operating Systems
- Object Oriented Programming
- Database Management
- Analysis of Algorithms
Semester 4:
- Time Series Analysis
- Cloud Computing
- Machine Learning Basics
- Data Warehousing
- Multidimensional Modeling
- Optimisation Techniques
Semester 5:
- Machine Learning Advanced
- Introduction to Artificial Intelligence
- Python Programming
- Data Visualization
- Big Data Analytics
Semester 6:
- Elective 1: Introduction to Graph Theory and Introduction to Statistical and Mathematical techniques.
- Elective 2: Cloud Computing and Business Project Management.
- Final Project
MS Data Science Syllabus
Below are the subjects in Data Science MS divided into four semesters:
Semester 1:
- Applied Statistics
- Data Science Fundamentals
- Spatial Science Mathematics
- Spatial Science Programming
- Python and R
- Statistical Inference
- Probability and Probability Distribution
- Computational Mathematics
Semester 2:
- Categorical Data Analysis
- Analysis and Design
- Distributed Algorithms
- Basics of Linear Models
- Linear Regression Models
- Optimisation Techniques
- Stochastic Process
Semester 3:
- Bayesian Statistical Model
- Longitudinal Data Analysis
- Machine Learning
- Deep Learning
- Text Mining
- Predictive Analysis
Semester 4:
- Applied Data Analytics
- Web Analytics
- SAS Programming for Analytics
- Artificial Intelligence
- Research Methodology
Data Science Course Fees
The fee structure for the Data Science course may vary from institute to institute and depends on whether you are going for an online or offline system. Below is the Data Science course fees structure at different levels:
- Under Graduate: ₹32.10 K to 35.64 Lakhs
- Post Graduate: ₹15.00 K to 13.60 Lakhs
- Doctoral: ₹31.50 Lakhs
- Diploma: ₹45.00 K
Conclusion
To conclude, Data Science is the most sought-after career, and the demand for Data Scientists is increasing rapidly in almost every field. Looking at the increasing demand for Data Scientists worldwide, nearly every institution offers courses in Data Science at Bachelor's, Master's, Diploma, and Doctoral levels. The article explains the Data Science subject syllabus and the general fees idea for aspirants. You can opt for this course from Newton School and get your Master's degree in Data Science from IU University and LSBU.
