Top 6 Data Analytics Courses at Coursera With Practical Examples

A degree in data analytics prepares individuals for a job in the industry. Data analytics programs are from beginning to advanced levels and are intended for individuals who want to be established as data professionals and wish to further their careers or individuals looking to pivot into the industry. This article will teach you more about various data analytics courses at Coursera if you should pursue one, and the various sorts of degrees available to you. You’ll also find suggested courses at the end to help you get started right away.

Data Analytics Courses at Coursera With Practical Training

Data analytics is a branch of data science. The goal of data analytics is to derive insights from data by linking patterns and trends to organizational goals. Data analytics is commonly used to compare data assets to organizational hypotheses, and the activity is typically centered on business and strategy. Data analytics is concerned with viewing historical data in context rather than with AI, machine learning, and predictive modeling.

We’ve produced a selection of the best data analytics courses at Coursera if you’re wanting to improve your skills for a job or leisure. Coursera is one of the world’s leading online education platforms, collaborating with over 200 universities and businesses to offer a variety of learning opportunities. The platform boasts over 77 million learners worldwide. 

Before we get into the details about data analytics courses at Coursera, let us first understand data analytics and its uses.

About Data Analytics & Its Uses

The collection, transformation, and organization of data to make forecasts, and drive informed decision-making is known as data analytics.

Data analytics is frequently mixed up with data analysis. While they are related concepts, they are not identical. Data analysis is a subset of data analytics that focuses on extracting meaning from data. Data analytics encompasses procedures other than analysis, such as data science (using data to theorize and forecast) and data engineering (building data systems).

Uses of Data Analytics

Data is all around us, and we utilize it every day, whether we recognize it or not. Daily actions like weighing coffee beans to create your morning cup, checking the weather forecast before deciding what to wear, or tracking your steps throughout the day with a fitness tracker are all examples of data analysis and its use.

Data analytics is crucial in many industries since many business leaders rely on data to make sound decisions. A sneaker manufacturer may use sales data to select which designs to keep and which to retire, while a healthcare administrator may examine inventory data to determine which medical supplies to order. Enrollment data may be used by educational institutions to determine what types of courses to add to their portfolio.

Companies that use data to drive their strategy are frequently more confident, aggressive, and financially astute.

Key Principles in Data Analytics

There are four forms of data analytics: descriptive, diagnostic, predictive, and prescriptive.

  • Descriptive analytics explain what occurred.
  • Diagnostic analytics explain why something occurred.
  • Predictive analytics forecasts what will most likely occur in the future.
  • Prescriptive analytics directs our actions.

These four types of data analytics, when combined, can assist a business in making data-driven decisions.

People that deal with data analytics will often investigate each of these four areas utilizing the data analysis process, which includes defining the question, gathering raw data, cleaning data, analyzing data, and interpreting the results.

Masters Vs. Bachelor’s Degree in Data Analytics

A master’s degree in data analytics is quite comparable to a bachelor’s degree in data analytics. However, there are certain major distinctions that degree candidates should be aware of. To begin, a master’s degree in data analytics and a bachelor’s degree in data analytics will cover much of the same subject, such as data analysis, computer science, and statistics. However, depending on the curriculum, some master’s programs may cover these topics in greater detail or complexity, while others may cover what was studied in an undergraduate year of study.

Second, the deadlines for a master’s degree and a bachelor’s degree are considerably different. A master’s degree typically takes one to two years to finish. A bachelor’s degree, on the other hand, typically takes four years to complete and includes extra subjects through course requirements such as liberal arts, sciences, and electives.

Scope of Data Analytics

Because there are more available positions for data analysts than persons with the necessary expertise, data analytics specialists are in great demand. Careers in data analytics industries are predicted to expand further in the future.

Data Analytics Entry-level Jobs Include Positions Such as:

  • Data analyst trainee
  • Data analyst associate
  • Data scientist in training

As You Get More Experience in the Field, You May Be Eligible for Mid- to Upper-level Positions Such as:

  • Analyst of data
  • Scientist of data
  • Data Architect 
  • Data scientist
  • Business Analyst 
  • Marketing expert

Now before we give you details about data analytics courses at Coursera, let us know a little about Coursera.

About Coursera

Coursera collaborates with over 275 premier universities and corporations to provide individuals and businesses worldwide with flexible, inexpensive, job-relevant online learning. They provide various learning opportunities, including hands-on projects and courses, job-ready credentials, and degree programs.

Coursera was launched in 2012 by Daphne Koller and Andrew Ng to give life-changing learning experiences to learners all around the world. Coursera is now a worldwide online learning platform that provides anybody, anywhere with access to online courses and degrees from top institutions and corporations. Coursera obtained B Corp designation in February 2021, which means that they have a legal obligation not only to their shareholders but also to make a good influence on society, as they work to decrease obstacles to a world-class education for everybody.

Coursera has 107 million learners and over 7,000 universities, corporations, and governments using it to access world-class learning anytime, anywhere.

Coursera collaborates with over 275+ renowned universities and corporations to provide individuals and businesses worldwide with flexible, affordable, job-relevant online learning.

Get on-demand lectures for PC and mobile—whenever and wherever you want. There are free classes, hands-on projects, certificate programs, and stackable credentials to choose from.

More Professional Courses 

Let Us Go Through Some of the Data Analytics Courses at Coursera

The first course in the list of data analytics courses at Coursera is Google Data Analytics Professional Certificate.

1. Google Data Analytics Professional Certificate

About the Course

Prepare for a new profession in the fast-growing field of data analytics, with no prior experience or education required. Get professional training designed by Google and the opportunity to network with renowned companies. 

Over the course of eight courses, you will learn in-demand skills that will prepare you for an entry-level job. You’ll hear from Google employees whose backgrounds in data analytics have served as springboards for their careers. If you work less than 10 hours per week, you can complete the certificate in less than 6 months.

Professional Certificates on Coursera can help you get a job, whether you want to start a new career or change your present one. Learn at your own pace, anytime and wherever suits you best. Enroll and take advantage of a 7-day free trial to discover a new career path. Your membership may be terminated or cancelled at any time.

Practical Projects

Build a portfolio that displays your work readiness to potential employers by using your talents with hands-on initiatives. You must finish the project to earn your Certificate (s).

Obtain a Professional Certification

When you finish all the program’s courses, you’ll receive a Certificate to share with your professional network and have access to career support tools to help you get started in your new job. Many Professional Certificates have employment partners who recognize the certificate, and others can help you prepare for a certification exam. 

The second course in the list of data analytics courses at Coursera is IBM Data Analytics with R Professional Certificate & Excel.

2. IBM Data Analytics with R Professional Certificate & Excel

This Professional Certificate is designed for anybody looking to gain job-ready abilities, tools, and a portfolio for a position as an entry-level data analyst or data scientist. Through these eight online courses, you will dive into the role of a data analyst or data scientist and develop the necessary skills to work with a variety of data sources and apply powerful tools such as Excel, Cognos Analytics, and the R programming language to become a data-driven practitioner and gain a competitive edge in the job market.

Throughout the program, you will conduct hands-on labs and projects to get practical expertise with Excel, Cognos Analytics, SQL, and the R programming language and related data science libraries.

Projects:

  • Using pivot tables, analyze fleet vehicle inventory data.
  • Create an interactive dashboard using key performance indicator (KPI) data from car sales.
  • Recognize patterns in countries’ Rates of COVID-19 testing data using R
  • To investigate foreign grain markets, use SQL in conjunction with the RODBC R package.
  • To predict precipitation, use linear and polynomial regression models and compare them to weather station data.
  • Create a dashboard that explores trends in census data using the R Shiny package.
  • To study how weather impacts bike-sharing demand, use hypothesis testing and predictive modeling abilities to create an interactive dashboard with the R Shiny package and a dynamic Leaflet map widget.

The third course in the list of data analytics courses at Coursera is Introduction to Data Analysis by Coursera Project Network.

Also read,

3. Introduction to Data Analysis by Coursera Project Network

Using sales data from a representative company, you will study the fundamentals of data analysis with Microsoft Excel in this project. You will learn how to reorganize your data and get precise information about it by using sorting and filtering tools. You’ll also learn how to use functions like IF and VLOOKUP to produce new data and connect data from other tables. Finally, you will learn how to create PivotTables to summarize and compare data. These abilities will enable you to execute data analysis efficiently on a wide range of data types and will serve as the foundation for expanding your toolkit as you investigate various data analysis strategies.

  • You will create an account with Microsoft Office 365 online and upload a document in this Free Guided Project.
  • To perform rudimentary data analysis, use sorting and filtering tools.
  • To execute more advanced data analysis, use functions such as IF, VLOOKUP, and PivotTables.
  • In a job interview, emphasize your practical experience.

The fourth course in the list of data analytics courses at Coursera is Excel Competencies for a Specialization in Data Analytics and Visualization.

4. Excel Skills for Data Analytics 

This course will help you enhance your analytical and visualization skills, allowing you to not only increase your present job performance but also extend your future job opportunities. Those in business and data analysis who wish to learn sophisticated Excel and Power BI will have an advantage in the job market.

After finishing this specialization, you will be able to use advanced Excel functions, imaginative visuals, and strong automation capabilities to bring data to life. These classes will provide you with a full collection of tools for data transformation, connecting, and analysis. You will be able to create stunning interactive dashboards and master a variety of charts. Finally, you will uncover a new dimension in Excel with PowerPivot, Get and Transform, and DAX.

Working with datasets that are like those found in the industry, you will use sophisticated Excel tools to shape the data, generate meaningful visualizations, and develop dashboards and reports to convey your findings. You will learn how to build a data process to automate your research and make the results more flexible and reproducible.

The fifth course in the list of data analytics courses at Coursera is Excel to MySQL

5. Excel to MySQL

This Specialization will teach you how to phrase business concerns as data inquiries. You’ll analyze data, construct forecasts and models, design visualizations, and present your findings using powerful tools and approaches including Excel, Tableau, and MySQL. In the final Capstone Project, you will examine and justify improvements to a real-world business process using your knowledge and skills.

The Capstone Project focuses on maximizing residential property profits, and Airbnb, our Capstone’s official Sponsor, provided feedback on the project design. Airbnb is the biggest platform for short-term rental transactions. Each year, the top ten Capstone participants will get the opportunity to present their work live to senior data scientists at Airbnb for criticism and debate.

More Recommended Reads

The next course in the list of data analytics courses at Coursera is Data Analysis with Python.

6. Data Analysis with Python

Data Scientists and Data Analysts must be able to analyze data in Python. This course will take you from the fundamentals of data analysis using Python to the creation and evaluation of data models.

The Following Topics Are Covered: 

– Data collection and import 

– Data cleaning, preparation, and formatting 

– Data frame manipulation

– Data summarization

– Developing machine learning regression models 

You’ll learn how to import data from various sources, clean and wrangle data, do exploratory data analysis (EDA), and build meaningful data visualizations. You will then learn how to anticipate future trends from data by creating linear, multiple, and polynomial regression models and pipelines, as well as how to assess them.

You will learn and practice utilizing hands-on laboratories and projects in addition to video lectures. To import, handle, analyze, and visualize fascinating datasets, you will use many open-source Python modules, including Pandas and Numpy. You will also design machine learning models and make predictions using scipy and scikit-learn.

Coursera has lots of options to choose from when it comes to any kind of courses including Data Analytics courses from top universities and industries to help you get started or develop in your Data Analytics career.

Let us see a few questions that you might have before pursuing data analytics courses at Coursera

Frequently Asked Questions

Q1. Is a master’s degree in Data Analytics beneficial?

A degree in data analytics may be well worth the effort depending on your goals, finances, and history. It could also be a needless detour that you don’t need to take to get to your destination. A master’s degree is typically appropriate for persons who do not already hold a bachelor’s degree in data analytics or who seek to continue their academic studies in data analytics. Individuals with a bachelor’s degree in a relevant field, such as statistics or computer science, may consider pursuing a master’s degree in data analytics to get a deeper grasp of the topic and to advertise their skill set to potential employers.

A bachelor’s degree may be adequate for job seekers to secure a position. A master’s degree, on the other hand, may favorably showcase your skills and abilities to companies, making you a more competitive applicant overall. A company may even explicitly require a master’s degree for senior roles. 

Q2. What are the job opportunities in data analytics?

If you’re new to the profession of data analysis, your initial employment could be as a junior analyst. You may be able to get hired as a data analyst if you have past work experience and transferable analytical skills.

A degree in data analytics can equip you for a range of jobs. While some of these occupations can be obtained with a bachelor’s degree in data analytics, more senior positions may necessitate an advanced degree, such as a master’s.

Here Are Some of the Jobs You Could Get With a master’s degree in Data Analytics:

  • Data analyst 
  • Business analyst 
  • Data scientist 
  • Statistician 
  • Business systems analyst
  • Business intelligence analyst

Many Data Analysts like the ability to work remotely or migrate easily, even globally. The nature of the employment itself is totally up to the person, but the income, benefits, and job stability are substantial.

Q3. Should I opt for an online or classroom-based course for data analytics?

Just as there are multiple reasons to pursue a master’s degree in data analytics, there are numerous types of master’s degrees that you might pursue. If you wish to be a graduate student, you should think about these three sorts of programs before applying:

Data Analytics Master’s Degree in Person

A program in which you attend classes with your classmates in a real-world classroom is known as an in-person master’s degree. As a result, this alternative offers a more typical college experience, including more face-to-face interaction with peers and instructors, frequently allowing for more direct assistance and networking opportunities. In-person degrees, on the other hand, are frequently more expensive and more rigorously controlled than other program kinds.

Online data analytics master’s degree

Because of the flexibility that online courses allow the participants and the requirement of attendance, online master’s programs are becoming increasingly popular. While some programs have standard application deadlines, others may have more flexible admissions requirements that allow applicants to submit on a rolling basis. While these programs typically provide more flexible schedules and lower costs, they may offer less chance for networking and mentorship than more traditional options.

Hybrid programs

A hybrid graduate program combines features of on-campus and online programs to give students more flexibility in completing course material while also providing more networking opportunities. Depending on your circumstances and personal goals, a program of this type could provide the best of both worlds and be a more diluted version of your ideal program that does not meet your requirements.

Conclusion

To master data analytics, you must learn everything you can. Whether you prefer to pursue a bachelor’s or master’s degree, this article lists various data analytics courses at Coursera that you can choose from.

A professional certificate or certification demonstrates your skills to current and prospective employers. Consider taking a flexible online course from the list of data analytics courses at Coursera to strengthen your analytic skills.

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