What is a Data Science Course?

Today, you will know that data science is essential to many industries. It has given large amounts of data that get produced. You may find this topic one of the most debated topics in the IT sector. In the past few years, data science has grown its popularity. Data Science Courses In Bangalore can be great for learning data science. Many companies are implementing data science techniques to grow their business and increase customer satisfaction.

What Is Data Science?

Data Science is referred to as a significant branch of study that notably deals with data by using important modern tools as well as techniques. People make good use of such techniques in order to find unseen patterns. With this, they get meaningful information and then come up with notable business decisions. It makes good use of complex machine learning algorithms with the intention of using predictive models. The company receives data from several sources for analysis and presents it in different formats.

Lifecycle Of Data Science

The lifecycle of data science has five distinct stages, and every stage has a different task:

  • Capture

Capture is the first stage which involves gathering raw structured and unstructured data. It includes steps like Data Acquisition, Entry, Signal Reception, and Data Extraction.

  • Maintain

Maintain is a stage that helps take the raw data and put it in a form that can be used for processing. It contains steps like Data Staging, Data Architecture, Data Warehousing, Data Cleansing, and Data Processing.

  • Process

The third stage is where data scientists use prepared data to examine its patterns, ranges, and biases. Further, they will determine how useful it will be for predictive analysis. It includes steps like Data Summarization, Data Mining, Data Modeling, and Clustering/Classification.

  • Analyze

Analyze is the fourth stage which involves performing various analyses of the data. It includes steps like Text Mining, Qualitative Analysis, Confirmatory, Regression and Predictive Analysis. 

  • Communicate

Communicating is the final stage in which analysts help to create data in an easily readable format. It has steps like Decision Making, Data Reporting, Data Visualization, and Business Intelligence.

Required Knowledge For Data Science

Following are some technical concepts which you should learn before you start learning data science:

  • Databases

A good data scientist should know about databases, know how to manage them, and how to extract data from them.

  • Programming Languages

You need to have some knowledge of programming languages. You can take a Python AI Ml Course in Pune to learn programming languages. Python is a common programming language because it is easy to learn and supports multiple data science and machine learning libraries.

  • Machine Learning

Machine Learning is very crucial for data science. Every data scientist has deep knowledge of machine learning. 

  • Modelling

Mathematical models allow you to make fast calculations and predictions based on the data you have for creating models. It is also a part of Machine Learning where you need to identify algorithms. Those algorithms should be suitable to solve a given problem.

  • Statistics

Statistics is important to handle the data that will help you in extracting a lot of intelligence as well as meaningful results.


Data Science is one of the trending courses in the developing world. It helps to discover patterns and trends in large datasets. You should have prior knowledge of databases, programming languages and some important parts. You also need to understand machine learning algorithms.