Syllabus of Data Science

Syllabus of Data Science

We live in a world where data is power. With social media having an impact on every aspect of our lives, even brands and organizations rely heavily on data to make decisions. There is a huge difference in collecting raw data and using that data in a comprehensive and structured way. The latter is harder and that’s why there is a growing demand for professionals who have the required knowledge of data assimilation along with the knowledge of tools and algorithms that will help decode patterns. The importance of data scientists in recent years has made it a lucrative option. With any discipline, it is important that you make an informed decision about what you will be getting into. The same holds true for data science so if you are planning on pursuing a data science course it is important that you have a fair knowledge of the course syllabus.


The syllabus of data science is the perfect amalgamation of business acumen, statistics, algorithms, machine learning techniques and tools that will help you in understanding how to identify patterns and gain insights from raw data. This skill becomes instrumental because this information will help the organization make informed and big decisions relating to their business.

The syllabus of data science is not just limited to the structuring of data in a comprehensive manner. It can be extended to analyzing data that involves both unstructured and structured data. The algorithms and tools taught through the course will help you in understanding the predictive analysis aspect of data science. These predictions are used in modeling the business structure. Predictive analysis uses historical data to analyze and predict the upcoming trends in the market. This information can be used to influence the present way of handling business as well as help them make future decisions. 

The syllabus of data science is designed in such a way that you get the required knowledge in the field of business knowledge, tools, and statistics and are well equipped to face the challenges of any organization in the industry. The skill-set acquired during the trajectory of this course is indispensable to becoming an asset in the field of data science.

Also Read:  SOP for MS in Data Science


The syllabus of data science offered by most universities is classified into 3 core components whose function is to help you adapt to both the theoretical and practical aspects of it. There are a number of skills that you can learn over the course of the program that will give you a better understanding of the field of data science. The syllabus of data science includes-


This part of the syllabus of data science focuses on engaging students with Big Data tools and techniques so that unstructured data can be converted to structured data. Big data consists of unstructured data collected in the form of clicks, videos, orders, comments, images, RSS fields, articles, etc. In the case of comparing different products with the help of web API‘s and RSS feeds you can access data from different websites for that product. This data is then presented after it’s structured out of its earlier format.


This part of the syllabus of data science comprises of mathematical models and algorithms that are employed to code machines so that they can adapt to everyday developments and face the challenges of an organization. It is also used for predictive analysis and for time series forecasting because it can be very useful in financial systems. It uses historical data patterns to predict future outcomes over the course of a few months or a year. 

Also Read: Masters in Machine Learning 


After an organization assimilates and collect tons of data daily, it is important that they have professionals who can carefully analyze and present this data in the form of visual reports and graphs so that the data can be used effectively for making good business decisions. It is important that you keep developing your knowledge about the business aspect of the process so that the patterns and insights can be better understood and used to make trends and bring about changes.


If you plan to pursue a data science course some subjects will be essential to your learning experience and fundamental for your understanding of the course. These are-

  • Data Science: Introduction and Importance
  • Data Scientist Roles and Responsibilities
  • Data Acquisition and Data Science Life Cycle
  • Deploying Recommender Systems on Real-World Data Sets 
  • Experimentation, Evaluation and Project Deployment Tools
  • Predictive Analytics and Segmentation Using Clustering 
  • Algorithms Used in Machine Learning
  • Working on Data Mining, Data Structures, and Data Manipulation
  • Big Data Fundamentals and Hadoop Integration with R

The field of data science is growing at an unprecedented rate and has a lot of scope for further growth if you decide to dive into it.  While we have given you an insight into what the field of data science holds for you, the syllabus of data science can vary in different colleges even if the core subjects stay the same. So if you wish to pursue data science and are confused about how to go about it, let the counselors at Leverage Edu help you make the right decision and shortlist the best colleges for you.

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