Top 10 Courses Indians Choose to Study Data Science in 2022

Introduction

Top 10 Courses Indians Choose to Study Data Science in 2022 : Data Science is a multidisciplinary entity responsible for the process of analysing large datasets to remove the functional implications of large data sets. In other words, Data Science can be defined as research information developed from a combination of data sources (well-structured and structured), and how this information can be transformed into an important tool that can ignite Company and IT approaches.

Data Science is critical to business development as it assists businesses to harness the power of Big Data in their overall vision and enables them to make informed business decisions. Detailed introduction to Data Science can help businesses manage costs, improve efficiency, and limit new market opportunities; allowing them to gain a competitive advantage over their competitors.

Roles and Responsibilities of a Data Scientist?

Data scientists work closely with business stakeholders to understand their goals and explain how data can be used to achieve those goals. Data design techniques create predictive algorithms and models to remove data from business requirements and help analyse data and share intelligently and equitably. Although each project is unique, the data collection and translation method generally follow the following method:

1. Ask polite questions to begin the discovery process
2. Get the data
3. Organise and clean up data
4. Enter and save data
5. Initial data analysis and analysis of test data
6. Select one or more models and algorithms
7. Use data science methods, such as machine learning, mathematical modelling, and practical ingenuity
8. Rate and improve results
9. Present final results to participants
10. Make changes based on feedback
11. Reuse the problem-solving method.

What is Data Science?

In simple terms, data science is defined as the process of obtaining important information from organised and unstructured data through a variety of tools and techniques. Other techniques used in data science include data extraction, data analysis, data mining, and data retrieval, to produce instructive results. The person who performs such types of tasks is called a data expert. In addition, it is widely used for decision-making and prediction through word analysis, machine learning, and causal prediction analysis.

Why Data Science?

With the advent of more information, it will be difficult to get the exact type of data needed to make business decisions. Today, a lot of data is unorganised and one can get a lot of unwanted data when extracting information. Here is the importance of data science. Nowadays, almost every organisation has hired a data scientist to test their previously inaccessible data. Therefore, every company has recognized the importance of hiring a data scientist, which has increased the need for certified and qualified data scientists. Data scientists are the most sought after professionals in the world and one can benefit more than any other expert.

Applications of Data Science

Here are the Data Science Applications:

1) Detection of Fraud and Risk: Over the years, financial institutions have learned to assess the likelihood of threats and crashes by including customer profiles, past costs, and other variables available with the data.

2) Healthcare: Data science facilitates the management and investigation of a wide variety of databases in health care approaches, drug development, medical image analysis, and more.

3) Internet Search: All search engines, like Google, use [data science] algorithms to provide the best results for the queries tested within a bit.

4) Targeted Promotion: Digital advertisements have a higher value-added value (CTR) than authorised ads because targeted promotions are established through one-time user behaviour with the help of data science algorithms.

5) Recommendations: Internet colossi and its affiliates are committed to the use of search engines to improve their results based on the final results of users’ queries and their interests.

6) Refined image, speech, or character recognition: Facebook face recognition algorithms, speech effects, such as Siri, Cortana, Alexa, and more., And Google Lens are all excellent examples of data science applications in photography, speech, and punctuation…

7) Games: Today, games use machine learning algorithms to improve themselves or improve themselves as players move up to the highest levels. In a moving game, the attacker (computer) can analyse the player’s previous movement and as a result, shape his or her game. All of this is possible because of the science of data.

8) The unpopular reality of taxpayers we see (AR): Additional facts promise a happy future with Data Science. A VR headset, for example, combines algorithms, data, and computer information to present the best viewing information.

Why is Data Science Important?

To bring about the benefits of business transformation and growth around the world, Data Science is essential. It helps to analyse data from large amounts of data.

Data Science is also changing the healthcare sector. It helps physicians to obtain medical diagnostic data and report symptoms to diagnose diseases early and can provide better treatment.

Today, Data Science is growing rapidly to take over all sectors whether health, media, supply chain, tech, etc. all around the world.

Top 10 Data Science Courses in India in 2022

1) Data Science Foundations by Great Learning

This is the free course by Great Learning you can enrol for this course by visiting the website of Great Learning (Mygreatlearning.com). The duration of this course is one hour. Data science in today’s world is a complete necessity and not just to add value. Whatever the domain you are working on, there will be data therefore, there will be a need to get details on this data. Data Science is a field that uses methods and algorithms to extract information from the data provided either structured data or informal data.

Due to the growth of data and the evolution of technology, the Data Science domain has seen a dramatic increase. In this lesson, we will first understand the importance of machine learning and then look at the two algorithms which are linear regression and object alignment. After completing the video lecture for one hour you have to pass a quiz and after obtaining at least a pass number on Quiz you will get a Certificate which you can share in your resume or CV etc. The level of the course is for Beginners.

The syllabus of the course which you will study are –

• Introduction to Machine Learning
• Linear Regression
• Linear regression – Mathematical concept
• Classification Algorithm – Logistic Regression

2) Data Science with Python (Great Learning)

The course contains 11.6 hours of video content level. This course is for beginners. This course is offered by MyGreatlearning.com and this course is free you can enrol for this course from Great Learning. This Python with Data Science course outlines the Python editing bases and various packages required for data science.

Syllabus of the course which you will study :

• Descriptive statistics
• Understanding distributions and plots
• Univariate statistical plots and usage
• Bivariate and multivariate statistics
• Intro to python
• Variables
• Operators
• Data types and strings in python
• Tuples
• List
• Dictionary and set in python
• Python functions and classes
• Intro to NumPy array
• Intro to linear regression
• Relationship between independent variable – and the target variable
• Coefficient of correlation
• Linear regression assumptions
• Introduction to logistic regression
• Sigmoid curve and log loss function
• Model cases of logistic regression

This comprehensive Python with Data Science course gives you an in-depth understanding of Python systems and mathematical foundations, needed to build a solid foundation and begin your journey towards becoming a successful data scientist. This Python with Data Science course outlines the Python editing bases and various packages required for data science. It also includes statistical distribution statistics as well as static, bivariate, and multivariate statistics. You will then learn a basic data science method called regression.

3) Data Science Basics for Absolute Beginners (Great Learning)

As the course title itself says Data Science For Absolute Beginners so people or learners who are beginners and have knowledge about Data Science or its course then it will be the best course which you can enrol for the speaker of this course is Mr Anirudh Rao. The course contains one hour of video lectures and thus the course is free. You can enrol for this course easily from mygreatlearning.com so till now more than two thousand plus learners have enrolled for this course. This is a free certified course which is offered by Great Learning platform.

To study the depth of the Data Science course first you have to study the basics or concepts of DS.

Statistics: Data Science is about statistics. You have to be good at least in basic concepts like definition, median, mode, plural, minimum, diversity, diversity, cohesive. So, start learning these concepts

Mathematics: We use a few mathematical concepts such as Linear Algebra, Vector Algebra, Calculus, Matrices.

Planning: Finally after learning the theory you need to automatically perform these tasks. That’s the job of a Data Scientist. So, learn the language of planning. R – if you come from a non-technical background and Python – if you are good at programming and understand the concept of oop. Also, you need to understand a few machine learning concepts. There are a few YouTube channels that show machine learning from the basics.

After completing DS Basics for Absolute Beginners from Great Learning you will be provided with a shareable certificate which can be shared by you in your resume etc.

4) Popular Applications of Data Science ( Great Learning)

Data Science is a field of research that combines mathematics and statistics to produce accurate data. It provides a large amount of complex data.

Data science is a process that includes:

Capture data including data acquisition, installation and extraction. Data storage includes data cleaning, editing, processing and architecture. Data processing includes data mining, compilation, modelling and summarising. Data analysis involves predicting data analysis, retrieval, text mining and quality analysis. Data communications include data reporting, visualisation, business intelligence and decision-making.

So to understand the process behind data science you have to know applications first you enrol for this course Popular Applications of Data Science from Mygreatlearning.com this course is free and the duration of this course is one hour which contains a video lecture after completing the video portion you have to go through a quiz in which you have to get at least have to obtain the passing number and after that, you will be provided with a shareable certificate.

5) Python for Data Science (Great Learning)

Python for Data Science this course is offered by the Great Learning platform the course is free and the level of the course is for Beginners. The course contains two hours of the video lecture and after completing the video you have to pass a quiz. After passing a quiz you will get a certificate which will be shareable. More than thirteen thousand plus learners have enrolled for this course on mygreatlearning.com .

Topics which you will learn in this course :

• Why Data Science
• Why learn Python
• Popular Python packages
• NumPy and Pandas theory and hands-on
• Data Science Architecture
• Components in Data Science
• Career in Data Science
• Skills needed to learn Python
• Introduction

Python is an important tool for learning data science, the most widely used programming language for data science. Provides multiple libraries that solve business problems in a single line and in a short time. Python is considered the best introduction to a university student program because of its simple syntax.

This first step involves learning all the basic concepts in the system. These ideas do not need to be available only in Python and can also be used in other programming languages. Most programming languages ​​are similar, and knowing these similarities will make understanding Python easier. This will also be important in the future if you are looking to learn other programming languages. The basic concepts you need to learn in this section include variables, data types, tasks, tasks, situations, pitfalls, and much more.

6) Journey into Data Science Consulting (Great Learning)

Journey into Data Science Consulting is a free course offered by Great Learning the speaker of this course is Mr Vishranth Chandrashekar who is a Senior Data Science Consultant and fractal analytics. This is a beginner course. The duration of this course is one hour of video lectures you can easily enrol for this course on mygreatlearning.com.

You need to work on things you do not know. Avoid things that everyone knows as you will be competing with thousands of others. Knowledge of the industry background is the key to success, Consultation always requires strong knowledge of what you are going to do, as well as information provided to your client’s staff.

You need to convince the client of the amount of value that you are offering. You should automatically do/remove all common objects as much as possible.

Some real concerns a client will have;

1. Data Confidentiality.
2. Working on a critical day. They may require you to have a security permit.
3. Working with professional, business SAS licensed tools and more. (avoid cheap software items like that)
4. Being in the same time-space as possible to avoid delays, personal meetings more often than video conferences etc.

7) PG Program Preview – Data Science and Business Analytics by (Great Learning)

PG Program Preview – Data Science and Business Analytics the duration of this course is 13.5 hours including seventeen quizzes. After completing a video content of 13.5 hours you have to clear 17 quizzes to get a certificate of completion of this course. This course is free and is offered by Mygreatlearning.com. You can easily take this course from the Great Learning platform. More than seven thousand learners had already registered for this course.

Overview of the course which you will study :

• Program Overview
• Data Science and Analytics Introduction
• Python
• Statistics
• Data Visualisation using Tableau
• Linear Regression
• Logistic Regression
• Classification Models – Naive Bayes and KNN

Difference between Data Science and Business Analytics

Data Science is about mathematical knowledge and coding skills. You can solve complex data-related problems and have the ability to customise your solution.

Business Analytics focuses on decision-making based on data generated problem-solving. A data analyst/business analyst will have little to do with statistics and other skills needed to solve data-related problems and more about the data they produce.

Business statistics are about simplicity and making data science easily accessible to provide information and help make business decisions.

For example, if you want to know how to make your ads or marketing campaign more effective, you may want to use segregation from your targeted customers to create a unique strategy for each customer group. This can be a Business function or a Data Analyst.

8) Data Science in FMCG (Great Learning)

You can enrol for this course online on Mygreatlearning.com this course is free which is offered by Great Learning more than thousands of learners enrol for this course. The duration of this course is one hour and after completing the course you have to pass a quiz to get a shareable certificate of completing the course. This is a study of how Data Science, in a few of the many ways, breaks down, markets, evolution, how to improve digital production that supports and enhances the roadmap for an important change in the CPG industry. This study will provide captions based on real-world conditions, solutions and sector specifications, as well as what is needed to make an impact.

Overview of the course which you will study :

• Introduction to Transformations in FMCG through Data Science
• How does a CPG organisation work?
• How Data Science can create a strategic impact?
• Understanding and Modelling the problem
• Probability Distribution – Refresh
• Model, Parameters and Variables
• Gibbs Sampling Algorithm
• Technology framework
• Introduction to Optimising manufacturing in Digital Age
• Throughput Optimization
• Canonical form for Optimization Modelling

Through data analysis, FMCG industries help to understand marketing strategies to create a greater impact on targeted customers. Apart from that, FMCG industries can now even understand the various costs that industries will incur in business.

FMCG products that include the market today are based cleaning products, toiletries, toothpaste products, cosmetics and more. The FMCG sector in India includes pharmaceuticals, consumer electronics, cold drinks, packaged food products and chocolates.

The workplace is stable Regardless of economic changes or trends, people will always need FMCG products. The rapid production and high profitability of these assets mean that the jobs of graduate students in the FMCG have a level of job security that is unmatched by any other industry.

9) Data Science Roles by (Great Learning)

It is very necessary to know the role of data science so you can enrol on this free course which is offered by Mygreatlearning.com. The duration of this course is 1.5 hours of video content. Many learners have already registered for this course. In this course you will study :

• What is Data Science?
• Introduction to a Strategic Approach to Data Science Roles
• Data Science Project Stages
• Data Science is a team effort
• Data Science roles and responsibilities
• Key responsibilities of a Data Scientist
• Key characteristics of a Data Scientist
• The strategy
• Transitioning into Data Science Team
• Impact of Corona on Data Science

Data Scientist makes a profit with data, specialises in various tools and technologies such as machine learning, in-depth learning, practicality and solves business problems by introducing a business future forecasting model.

The data scientist works with mathematics and machine learning models as well as an automated Business Intelligence Organisation tool.

Data scientists are sometimes experts in technologies such as  Pig, Python, Hadoop etc Their work can focus on data management, analytics modelling, and business analysis. Because they tend to specialise in a small data science niche, data scientists often work in groups within a company.

10) SQL for Data Science by (Great Learning)

SQL for Data Science this course is a free course which is offered by the Great Learning platform you can enrol for this course from Great Learning. More than twenty-two thousand learners have already registered for this course. The duration of this course is 3.0 hours of video lecture. The level of this course is intermediate. After completing the video content you have to pass a quiz to get a certificate which you can share in your resume, CV or any other documents etc.

Syllabus of the course :

• Course Overview
• Intro to Clauses
• Group By Statement
• Demo for Group By Statement
• Having Clause Statement
• Demo For having Clause
• Alias in SQL
• Joins in SQL
• Types of Joins in SQL
• INNER Join
• LEFT Join
• RIGHT Join
• FULL Join
• SELF Join
• Intro to Subquery
• Problem Statement
• What is a Subquery?
• How Subquery Executes?
• Type of Subquery
• Demo for Subqueries
• Introduction to SQL with Python
• History of Python
• Why Should You Learn Python?
• Why is Python So Popular?
• Installing Python
• MySQL with Python Demo

SQL is one of the key skills a data scientist should have. SQL is the language of dealing with NoSQL related sites such as MySQL, Oracle DB, MS SQL Server, and MongoDB.

Data Scientists work on systematic data available on web servers. Therefore, it is important to connect data information using Python or R and drag data to create machine learning models. Using SQL commands, data scientists can store, retrieve, manipulate and update data.

Conclusion

Data Science is not a new fashion that makes cycles. Just because technology reshapes the industry and enhances its benefits. Today, it is possible to not only refer to previous data but also to make calculated calculations, and that is one of the most powerful aspects of Data Science.

Organisations now rely heavily on data. The following are the benefits of using Data Science in the company.

Data Science helps to understand market behaviour and customer sentiment. Finding patterns with available data can help launch marketing campaigns that are more tailored to what the audience wants.

Statistics can save a company from losses by predicting what lies ahead. It is commonly referred to as Risk Analysis and is part of Data Science. Decision-making is highly dependent on a company supported by an appropriate Data Analysis. That’s where Data Science turns into Business Analysis.