Data Analytics Courses for Beginners: Big Data Courses for Beginners, R Programming, Python, and MYSQL

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Collegedunia Team

Content Curator | Updated 3+ months ago

Data Analytics Courses for Beginners are usually short-term courses, which are specifically designed with R Programming, Python, and MYSQL. These programming languages in Data Analytics help beginners to gain knowledge about Data Analysis. Students will grow expertise in all the programming languages. 

Students can pursue Data Analytics Courses for Beginners from various reputed online platforms such as Coursera, Udacity, Udemy, and DataCamp. Platforms like Coursera and Udemy offer the top 10 best Online Data Analytics Courses for Beginners. 

1. Google Data Analytics Professional Certificate– Coursera

Provider Google
Rating 4.8/5
Time to Complete 6 Months (If students spend 10 hours/week)
Level Beginners
Programming Language R Programming

Throughout this program, students will learn the fundamentals of data analytics as well as common data analysis challenges. One of the most popular best data analytics certifications for beginners is the Google Data Analytics Professional Certificate. This program consists of eight courses. If students are a beginner interested in the R programming language, this is the program for students. Students will learn how to use spreadsheets in data analysis. Data analysis necessitates a number of steps, and one of these steps is data cleaning. Students will learn about SQL Data Cleaning. Those who are new to data analytics and want to learn the basics. Students will also receive Course Videos and Readings, Practice Quizzes, and Graded Assignments with Peer Review.

2. Intro to Data Analysis– Udacity

Provider Udacity
Rating NA
Time to Complete 6 Weeks
Level Beginners (But knows Python)
Programming Language Python Programming

This is not an advanced-level course, but it attempts to cover the fundamentals of Data Analytics. This course will teach students about Data Wrangling. This Intro to Data Analysis course is completely free and a good starting point for understanding the data analysis process. This course includes one project. Because this course is free, students are unable to submit their projects for review. However, students must complete this project for their understanding and portfolio. students will understand all of the steps involved in data analysis after completing this project. This is a free course, and students will not be charged anything to learn the fundamentals of data analysis.

3. Data Analyst with Python– DataCamp

Provider Datacamp
Rating NA
Time to Complete 32 hours
Level Beginners
Programming Language Python Programming

This course will teach students how to use popular Python libraries such as Pandas, Matplotlib, Numpy, and others. Students will have the opportunity to advance their Python knowledge by learning some advanced Python concepts. Datacamp offers a Career Track in Data Analyst with Python. There are eight courses in this career path. If students have no prior Python experience, this course is for you. Statistics knowledge is required for data analysis, and this career path teaches the fundamentals of statistics. Students will also learn about Seaborn, a Python library for creating visually appealing and informative visualizations. This career path also includes a skill assessment for data manipulation. DataCamp includes a console where students can code and practice.

4. IBM Data Analyst Professional Certificate– Coursera

Provider IBM
Rating 4.7/5
Time to Complete 11 Months (If students spend 3 hours/week)
Level Beginners (But Knows High-school level math)
Programming Language Python Programming

For those who want to learn Data Analytics with Python programming, this program is the best alternative to the Google Data Analytics Professional Certificate. Another excellent data analytics certification for beginners is the IBM Data Analyst Professional Certificate program. This program consists of nine courses. In this program, students will learn the fundamentals of Excel courses for performing basic data analysis tasks such as editing, moving, and copying data files. There is one capstone project that students must complete at the end of this program. This course teaches Cognos instead of Tableau for data visualization. Python has a data visualization library called Matplotlib.

5. Excel to MySQL: Analytic Techniques for Business Specialization– Coursera

Provider Duke University
Rating 4.6/5
Time to Complete 7 months
Level Beginners
Programming Language MYSQL

Throughout this program, students will learn Business Metrics and the fundamentals of Excel for data analysis tasks. Excel is a commonly used tool for performing data analysis operations. Duke University offers this Excel to MySQL: Analytic Techniques for Business Specialization program. This program consists of five courses. This program teaches data analytics techniques for business tasks. This program employs Tableau, the most popular tool for data visualization. The instructor also discusses Relational Databases and Big Data. This program also covers advanced topics such as linear regression, the Central Limit Theorem (CLT), Gaussian distributions, and so on. Course Videos and Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments are also included.

6. Beginner Statistics for Data Analytics- Udemy

Provider Udemy
Rating 4.6/5
Time to Complete 3 hours
Level Beginners
Programming Language NA

Sudents will learn the fundamentals of statistics, such as mean, median, and mode. Following that, students will be introduced to Descriptive and Inferential Statistics. This Beginner Statistics for Data Analytics course is designed for people who are new to statistics and want to learn the fundamentals of data analysis. Students will also learn about Regression Analysis. The instructor also covers standard deviation and correlation. In this course, Excel is used to perform all of these operations. Students will also receive three downloadable resources and lifetime access to the course material.

7. The Complete Introduction to Data Analytics with Tableau- Udemy

Provider Udemy
Rating 4.4/5
Time to Complete 7 hours
Level Beginners

The first project investigates the sale of an e-commerce business. The second project will use survey data to examine a company called Green Destinations and why its employees are leaving. Another data analytics certification course for beginners is the Complete Introduction to Data Analytics with Tableau. This is not an academic course. This is a comprehensive practical course in which students will work on five projects. This course focuses on Tableau, a data visualization tool. This project is beneficial to students’ resumes because students will work on five projects that students can include on their resumes. The instructor also explains Excel, Google Sheets, and Cloud Servers. students will also receive 32 downloadable resources.

8. Data Analysis and Presentation Skills: the PwC Approach Specialization– Coursera

Provider PwC
Rating 4.7/5
Time to Complete 6 months (3 hours/week)
Level Beginners

This program will teach students about Data Analysis tools, and techniques. The data analysis process in this program is carried out using Excel. PwC provides this Data Analysis Skills: the PwC Approach Specialization (Multinational professional services network). This program consists of five courses. This program employs advanced Excel for data visualization. Following the learning of these concepts, there is one Capstone Project in which students must understand and analyze a business problem. Students will also learn how to use PowerPoint for storytelling. Students will become acquainted with various communication styles. This is yet another Beginner Specialization Program. students don't need any prior knowledge. Anyone who wants to learn data analytics can enroll.

9. Intro to Data Analysis– Udacity

Time to Complete 6 Weeks
Programming Language Python

Python libraries Pandas, Numpy, and Matplotlib will also be covered. Because this course is free, students will not receive a certificate. This Intro to Data Analysis course is completely free and a good way to learn about the data analysis process. This course will cover the fundamentals of data analysis, from data collection to visualizing the results.

10. Data Analysis with R– Udacity

Time to Complete 2 months
Programming Language R

Although this is a free course, it covers a wide range of R programming and data analysis topics. This course will cover the fundamentals of EDA, its significance, and its objectives. This free intermediate-level Data Analysis with R course teaches data analysis using R programming. This course concludes with one project. students must conduct their own exploratory data analysis and create an RMD file for this project. Then students will learn the fundamentals of R programming. This course includes problem sets in which students must investigate One Variable and Two Variables.

Data Analytics Courses for Beginners: FAQs

Ques. Are Data Analytics Courses for beginners in demand?

Ans- Yes, these courses are well in demand as almost all companies today rely on data analytics to boost their net worth.

Ques. Are Data Analytics Courses for beginners tough?

Ans- No, a beginner-level course covers all the basic topics and fundamentals and is not tough if a candidate is interested in pursuing it further..

Ques. What is the difference between data analytics courses for beginners and a diploma in Data Analytics?

Ans- The Beginner level course will allow students to learn Data Analytics in a fundamental, easier, and less detailed way while a Diploma course is more specific in nature. It also allows students to specialize in a particular field.

Ques. Can I earn a good amount of money after completing a data analytics course for beginners?

Ans- Students will be able to earn good money once students have more knowledge in the field of Data Analytics.

Ques. Are online Data Analytics courses for beginners good?

Ans- Yes, the online courses are as good as offline courses. They are feasible, save money and even save time.

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