Data Analytics

Top 5 Data Analytics Courses After Graduation With Placement

The importance of data analytics has sparked more discussion among all professionals, particularly students and recent graduates. The demand for data analytics is exceeding the supply, thus increasing job opportunities for more freshers. As a result of this, searching for “data analytics courses after graduation” on the internet has become a viral phenomenon.


Do you know? 93% of the organizations have stated that they plan to continue their investment in data and analytics. It is the fastest-growing career in India as well as the rest of the world. The world is moving from traditional data dashboards to real-time data visualization.


Table of Contents

Who can become Data Analyst?

Data analytics career – Is it the right choice?

Data Analytics Courses

How to Become a Data Analyst with No Experience

Data Analytics Syllabus

Role of Data Analyst

Data Analyst Salary

The Future of Data Analysis

Data Analytics Job for Freshers

Skills required for data analyst

Top 5 online Data Analytics Courses After Graduation For Beginners

Frequently Asked Questions



Who Can Become a Data Analyst?

Data analytics means nothing more than transforming raw data into meaningful, actionable information. Think global! People from all fields need data, regardless of their industry; you name it. If you are reading this article, then you need data too. To become a data analyst, remember that this field needs innovative aspirants to deal with data. Let me group it widely into the following categories:

  • Willing to learn
  • Ready to work with numbers
  • Basic understanding of programming languages


If you satisfy the above two categories, or if you are someone looking for data analytics courses after graduation to upskill yourself, then your search ends here.


Data Analytics Career – Is It The Right Choice?

Many countries around the world have recognized the value of data analytics and have invested heavily in the field. Countries like India, the US, and China are the major investors in data analytics. Whether in organizations or government sectors, data analytics has become a global phenomenon as a way to support economic growth and enhance data security, which also impacts national security.

Choosing a career in data analytics will be the right choice for many professionals since there is rapid growth and demand in the field of data analytics and it offers a wide range of employment opportunities.

Another main and most important reason for everyone to look for data analytics courses after graduation is to get an opportunity, a nice future, and a nice paying job, which you will acquire by doing a data analytics course.


Data Analytics Courses

There are different kinds of data analytics courses after graduation, ranging from basic introductions to more advanced topics and even specialized topics. If you are looking for data analytics courses, here are a few:


Introductory data analytics courses: These courses provide an overview and the fundamentals of data analytics, including data cleaning and preparation, statistical analysis, and data visualization.


Advanced data analytics courses: These courses dive deeper into more complex topics and methodologies like predictive modeling, machine learning, and data mining.


Big data analytics: These courses cover the tools and techniques used to study large datasets, which include distributed computing, cloud computing, and Hadoop.


Business analytics courses: This training will focus intensively on the applications of data analytics to business factors.


Data visualization courses: This training especially focuses on designing and developing effective data visualization, including data presentation and storytelling.


Industry-specific data analytics courses: There are courses that specifically provide data analytics training with respect to specific industries, like health care, finance, and more.


Programming courses: To become a data analyst, you must have a basic understanding of programming languages such as Python, R, and SQL.


The above-mentioned courses are just a few examples of the various types of data analytics courses available, and it is more important to consider your own interests, career goals, and level of experience with data analytics. Another important thing is to make sure the courses are taught by industry experts.


How to Become a Data Analyst with No Experience

Becoming a data analyst without experience might be challenging, but it is possible if you have the right road map.

  1. Learn the fundamentals – Start with the basics of data analytics. You can take online courses. The data analytics courses cover major topics such as data visualization, statistics, programming skills, and a lot more.
  2. Practice with real data – Once you are familiar with the fundamentals of data analytics, practicing with real-time data is very important.
  3. Learn from the experts – Enrolling in a full-time training program will be beneficial as it will be taught by the experts.
  4. Build a portfolio – Since you work on a data analytics project, track your work and document your output. You can even create a website portfolio to showcase your work so you can share it with employers.
  5. Apply for Internship  – Look for an internship, that will add value to your portfolio. This is a great practice to gain practical experience. There are possibilities, where the employer might change you from being an intern to a full-time employee based on your dedication and work.
  6. Practice and Learn daily – Data analytics is an ever-evolving field, so it is very important to keep learning and enhancing your skill. Stay up-to-date with data analytics news. You can get daily updates if you become a member of forums and newsletters, and you can follow industry experts.


These above steps might consume some time, but if you work hard and are dedicated and persistent, you can definitely achieve your goal.


Data Analytics Syllabus

Mostly, students tend to take data analytics courses after graduation to enhance their skills and get placed in a well-paying job. Data analytics is a vast subject, and there are different data analytics courses after graduation that include quite a number of topics that one must cover to become an efficient data analyst.

The syllabus of the course might vary depending on the institute, the level of experience one has, and what one intends to learn. Let me give you the outline of the data analytics syllabus.


  1. Introduction to data analytics
●      Overview of data analytics

●      The importance of data analytics

●      Basic terminologies and concepts

  1. Data collection and cleaning
●      Types of data and sources of data

●      Methods to collect data

●      Cleaning data

●      Data validation

●      Quality assurance

  1. Data analysis and Interpretation
●      Descriptive statistics

●      Data visualization

●      Inferential statistics

●      Hypothesis testing

●      ML (Machine learning)

●      Regression analysis

●      Predictive modeling

  1. Data visualization and communication
●      Methods for data visualization

●      Tools and techniques

●      Communicating data effectively


Also, you will learn in-depth concepts of key analytical skills and you will learn tools like Preadsheet, SQL, R programming, and Tableau. Data analytics courses after graduation will give you an eye-opening for lots of opportunities, and once you complete the course, you will gain skills in data analytics, statistical analysis using Excel, data analysis using R and Python, data visualization with Tableau and PowerBI, linear and logistic regression modules, and a lot more.


Role of Data Analyst

The role of a data analyst plays a very important role in any organization. A data analyst is in charge of compiling, organizing, and evaluating details relating to market research, sales figures, logistics reports, and other organizational actions. Data analysts verify the data’s accuracy before analyzing and presenting it in a way that helps people and organizations make decisions.


  • Utilizing automated techniques to extract data from primary and secondary sources.
  • Removing bugs in the code and corrupted data.
  • Developing and maintaining the database.
  • Recognizing the data is in a readable format.
  • Doing regular analysis to assess the quality and meaning of data.
  • Data filtering by reviewing reports.
  • Identify and correct the bugs in the code using performance indicators.
  • Use statistical tools to identify, and analyze complex data sets to patterns and trends which could help in diagnosing and predicting.
  • Assigning numerical value to the essential business function so that the performance of the business can be assessed and predicted over the period.
  • Analyzing trends – National, global, and local to impact both the organization and the industry.
  • Data analyst is responsible to prepare reports, stating trends and patterns, and making predictions using relevant sources.
  • Need to work along with programmers, engineers, and people in the management to identify opportunities, process improvements, and work on strategies.
  • Need to prepare final analysis report for the stakeholders, enabling the stakeholders to take important decisions.


Job roles of data analysts also include an integral element called EDA (Exploratory data analytics) projects where the analyst penetrates deeper into the data to recognize and identify the patterns.


Data Analyst Salary

The data analyst makes a competitive salary across the globe. However, the data analyst’s salaries are determined by their experience, geography, profession, company’s growth, etc. Data analyst fresher salary can expect the range between Rs 45,000 per month to Rs50,000 per month

Senior data analyst salaries can range from 12 LPA to 24 LPA. Again, the data analyst salary mentioned above is just an ideal prediction, and salaries are determined by lots of other factors.

As a result, data analysts are in high demand across a wide range of industries, and if you are a student who has just completed data analytics courses after graduation, you are already in demand.


The Future of Data Analysis

Since it started, data analytics has been continuously evolving. During the initial stages of data analysis, it only dealt with descriptive analysis, which only stated data sets. Data analysis has evolved a lot since then. Data analytics is evolving rapidly, and the days when people used graphs, charts, and bars are fading away.

Many new techniques have been developed that have expanded the scope of data analysis to new heights. Advanced technologies like machine learning, automation, AI, and the Internet of Things (IoT) have significantly contributed to the enormous growth of data analytics.

There are many articles now about what to expect in the future of data analysis, what tools may replace existing ones, which technologies and platforms will be used, and so on. Industry experts have predicted the technologies and platforms that will shape data analytics, and they will play a vital role in the development of the industry.


Let me break it down for you:

Relationship analytics: In the future, with the help of relationship analytics, organizations can break down multiple datasets and analyze the data as a whole rather than in isolation. This will enable companies to get more comprehensive insights from their data analytics process.


Decision Intelligence: Decision intelligence is a robust platform that integrates social science, managerial science, and data science all into one.


Continuous analytics: This helps to take full advantage of the IoT devices, and this process will help to generate more insights even faster.


It is obvious that the future of data analytics is enormous. This field is still in its developing stages, and much remains to be discussed.


Data Analytics Job for Freshers

We are living in the data era. However, we are in the early stages of the future. This relates to the fact that data analytics is fundamentally altering how we live and how data analytics for businesses utilize their data to make choices. While considering the future scope of data analytics, the growth of the field will naturally result in the creation of new jobs.

Furthermore, it is very likely that the emphasis will shift from the requirement of degrees to individuals who demonstrate the required skills and have hands-on experience in the analytics field. Because there are so many different designations in the data analytics field, beginners who completed data analytics courses after graduation will have a better chance of getting hired.

The bottom line is that everything related to data is going to be the future of mankind. There are lots of rooms open for data analytics jobs for freshers. If you have the required skill, there will be no difficulty in getting a job since there is a huge demand for people in the field of data analytics.


Skills Required for Data Analyst

Let us see some of the common parts that you should be aware of. The actual skills might vary from employer to employer, but it is likely a mix of the following:


  • Technical Skills: You must gain confidence and knowledge of the various analytics tools.
  • Knowledge of statistics: You should have knowledge of the algorithm and understand why it is used.
  • Structured thinking: You should be able to solve ambiguous problems and put them into a framework.
  • Business understanding: How well you can apply your business-minded mentality to problem-solving
  • Problem-solving: You will be expected to provide an “out of the box” solution to the problems.
  • Communication skills: You should be able to deliver your thoughts in a clear way.
  • Ease with numbers: You should good at crunching the numbers.
  • Attention to details: You should pay attention even to small detailing.


Remember: Data analytics professionals are immediate explorers—self-driven and communicative. With this in mind, fresh graduates completing their data analytics courses after graduation should align their skills and knowledge.


Also Read:


Top 5 Online Data Analytics Courses After Graduation For Beginners


Rank #1. Data Analysis Courses After Graduation

1. Google Data Analytics Professional Certificate by Coursera

In this program, you will learn in-depth skills about data analytics that will make you job-ready. This program will teach you how to analyze data, analyze using tools, R programming, and data visualization.


Skills you will gain- Spreadsheet, Data cleansing, Data analysis, DataViz(Data Visualization), SQL, Questioning, Decision-Making, Metadata, Data collection, Data Ethics, and Sample size determination.

Mode of Learning – Online


Why Study from Coursera

  • This program covers all the major concepts of data analytics.
  • You will work on real-time projects.
  • This program is developed exclusively by the expert employees of Google.
  • This program will simulate real-world scenarios.


Level: Beginner to intermediate


Course Syllabus

Module 1: Foundations: Data, Data, Everywhere

Module 2: Ask questions to make decisions on Data-Driven

Module 3: Prepare data for exploration.

Module 4: Processing Data from Dirty to Clean

Module 5: Analyzing Data to Answer Questions

Module 6: Data Sharing through Visualization

Module 7: Data Analysis using R Programming

Module 8: Google Data Analytics Projects


Rank #2. Data Analysis Courses After Graduation

2. Become a Data Analyst – Linkedin Learning

LinkedIn Learning will provide you with more in-depth data analytics skills. This course mainly focuses on Microsoft tools like Excel and Power BI. Learners will gain a deeper understanding of statistics in this course, which will strengthen their math skills for analytics.


Mode of Learning: Online

Level: Beginner to intermediate.


Course Syllabus

Module 1: The non-technical skills of an effective data scientist

Module 2: Learning Excel for Data Analysis

Module 3: Data fluency for exploring and describing data

Module 4: Learning Data Analytics Foundation – Part 1

Module 5: Learning Data Analytics Foundation – Part 2

Module 6: Essential Training on Excel Statistics

Module 7: Data Mining – Predictive Analytics

Module 8: Learning Power BI

Module 9: Learning Data Visualization

Module 10: SQL – Data Reporting and Analysis

Module 11: Learning Tableau

Module 12: R Programming – Wrangling and Visualizing Data

Module 13: Data Cleaning


Rank #3. Data Analysis Courses After Graduation

3. Excel Skills for Data Analytics and Visualization Specialization from Coursera

This course, exclusively from Macquarie University, covers Excel modules from scratch and introduces advanced concepts that enable you to clean, analyze, and visualize data efficiently.


Mode of Learning: Online

Level: Beginner to Advanced


Course Syllabus

Module 1: Excel Fundamentals for Data Analysis

Module 2: Data Visualization in Excel

Module 3: Excel Power Tools for Data Analysis


Rank #4. Data Analysis Courses After Graduation

4. Data Analyst in R – Dataquest

For those who look for data analytics courses after graduation, this may fit many graduates who are interested in the programming side of data analytics. Dataquest is one of the most popular data analytics learning platforms.


Mode of Learning: Online

Level: Beginner


Course Syllabus

Module 1: Introduction to R syntax

Module 2: Data structures

Module 3: Loops, iterations, functions, and control flow

Module 4: Data visualization

Module 5: Data cleaning

Module 6: SQL Fundamentals

Module  7: Intermediate SQL

Module 8: Getting data from APIs and web scraping in R

Module 9: Statistics using R – Beginner to intermediate

Module 10: Probability fundamentals and conditional probability

Module 11: Hypothesis testing

Module 12: Linear regression

Module 13: ML fundamentals

Module 14: Interactive web apps with R


Rank #5. Data Analysis Courses After Graduation

5. Business and Data Analytics with SQL – Skillshare

The skillshare was created by veteran instructor Geoff Devitt, who has 20+ years of experience in the big data industry. This course mainly focuses on solving analytical problems using a structured query language (SQL).


Mode of Learning: Online

Level: Beginner to Advanced


Course Syllabus

Module 1: Introduction to database

Module 2: Normalizing Data

Module 3: Fact Tables

Module 4: Aggregating data

Module 6: Entity Relationship Diagrams(ERD)

Module 7: Setting up and connecting to MySQL

Module 8: Beginner to Intermediate SQL

Module 9: Data analysis project

Module 10: Query explain plans

Module 11: MySQL administration


Frequently Asked Questions


1) Why choose data analysis courses after graduation?

Data analytics has immense growth potential, and as a graduate, analytical skill is the most basic skill that one should possess.


2) What is the difference between Data Science and Data Analytics?

The major difference between data science and data analytics is the scope. They both deal with big data. Data analytics is the process of making use of existing data or resources, whereas data science deals with new exploration and innovative strategies.


3) How do beginners learn data analytics courses after graduation?

  • Learn the fundamentals of statistics
  • Start learning the fundamentals of programming
  • Learn problem-solving techniques


4) What are the jobs in data analytics for freshers?

According to LinkedIn, there are 99,000+ jobs available for the position of junior data analyst, and it is adding new vacancies as well. There is a huge scope for data analytics freshers.


5) What will be the duration of the data analytics courses?

It depends on the kind of program one enrolls in. But, usually, the duration of data analytics courses after graduation will be 6–7 months.



From a career perspective, for students who have gone through data analytics courses after graduation, data analytics is definitely one of the evident domains of world technology. Data analytics has become increasingly relevant in everyday scenarios, and the future of data analytics after graduation promises exciting career opportunities. This implies that the future of data analytics is brimming with the most enticing discoveries and still has room to explore more possibilities for data analytics services.

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