In this article, you will find the Best Data Analytics Courses on Coursera & advanced like Beginner courses, and Practice test courses. So, check these Best Data Analytics Courses on Coursera and find the Best Data Analytics Courses on Coursera for Beginners to Advanced according to your need. In the previous article, I have shared the Best Free Data Analysis Courses to know in 2022, you can go through the list and enjoy reading.
Here we have covered the Best Data Analytics Courses on Coursera. Let’s go through the list of Coursera Data Analytics Courses one by oone.
Best Data Analytics Courses on Coursera 2022
Google Data Analytics Professional Certificate – Google
Rating: 4.8
Over 8 courses, gain in-demand skills that prepare you for an entry-level job. You’ll learn from Google employees whose foundations in data analytics served as launchpads for their own careers. At under 10 hours per week, you can complete the certificate in less than 6 months.
You’ll prepare yourself for jobs that include junior or associate data analyst, database administrator, and more.
Get professional training designed by Google and prepare for a new career in the high-growth field of data analytics, no experience required.
- Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job
- Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming
- Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau)
- Learn how to visualize and present data findings in dashboards, presentations and commonly used visualization platforms
There are a total of 8 Courses in this Google Data Analytics Professional Certification course. They are:
- Foundations: Data, Data Everywhere
- Ask Questions to Make Data-Driven Decisions
- Prepare Data for Exploration
- Process Data from Dirty to Clean
- Analyse Data to Answer Questions
- Share Data Through the Art of Visualization
- Data Analysis with R Programming
- Google Data Analytics Capstone: Complete a Case Study
Best For: Beginners | Course Duration: 3 Months | Provider: Google
Info: Visit this course and get amazing offers on this course with Monthly and Yearly plans
IBM Data Analyst Professional Certificate – IBM
Rating: 4.6
This Professional Certificate does not require any prior programming or statistical skills, and is suitable for learners with or without college degrees. All you need to get started is basic computer literacy, high school math, comfort working with numbers, willingness to learn, and a desire to enrich your profile with valuable skills.
Upon successful completion of this program, you’ll have analyzed real-world datasets, created interactive dashboards, and presented reports to share your findings, giving you the confidence and the portfolio to begin a career as an associate or junior data analyst. You’ll also build the foundation for other data disciplines such as data science or data engineering.
You’ll work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics, gaining practical experience with data manipulation and applying analytical techniques.
- Demonstrate proficiency in using spreadsheets and utilizing Excel to perform a variety of data analysis tasks like data wrangling and data mining
- Develop working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services
- Create various charts and plots in Excel & work with IBM Cognos Analytics to build dashboards. Visualize data using Python libraries like Matplotlib
- Describe data ecosystem and Compose queries to access data in cloud databases using SQL and Python from Jupyter notebooks
There are a total of 9 Courses in this IBM Data Analyst Professional Certification course. They are:
- Introduction to Data Analytics
- Excel basics for Data Analysis
- Data Visualization and Dashboards with Excel and Cognos
- Python for Data Science, AI & Development
- Python Project for Data Science
- Data Bases and SQL for Data Science with Python
- Data Analysis with Python
- Data Visualization with Python
- IBM Data Analyst Capstone Project
Even if you are interested or if you need only one skill or one Subject or one course then you can enroll for that particular course and learn it easily which you need the skill
Best For: Beginners | Course Duration: 6 Months | Provider: IBM
Introduction to Data Analytics – IBM
Rating: 4.8
This course presents a gentle introduction into the concepts of data analysis, the role of a Data Analyst, and the tools that are used to perform daily functions. You will gain an understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering or data mining.
You will then learn the soft skills that are required to effectively communicate your data to stakeholders, and how mastering these skills can give you the option to become a data driven decision maker.
This course will help you to differentiate between the roles of a Data Analyst, Data Scientist, and Data Engineer. You will learn the responsibilities of a Data Analyst and exactly what data analysis entails. You will be able to summarize the data ecosystem, such as databases and data warehouses.
You will then uncover the major vendors within the data ecosystem and explore the various tools on-premise and in the cloud. Continue this exciting journey and discover Big Data platforms such as Hadoop, Hive, and Spark.
By the end of this course you will be able to visualize the daily life of a Data Analyst, understand the different career paths that are available for data analytics, and identify the many resources available for mastering this profession.
- Explain what Data Analytics is and the key steps in the Data Analytics process.
- Describe the different types of data structures, file formats, sources of data, and data repositories.
- Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst.
- Identify key elements in the Data Analytics process by analyzing a business case study and its data set.
Best for: Beginners | Course Duration: 10hrs | Provider: IBM
Info: Visit this course and get amazing offers on this course
IBM Data Analytics with Excel and R Professional Certificate
Rating: 4.7
This Professional Certificate is intended for anyone who is seeking to develop the job-ready skills, tools, and portfolio for an entry-level data analyst or data scientist position.
you will dive into the role of a data analyst or data scientist and develop the essential skills you need work with a range of data sources and apply powerful tools, including Excel, Cognos Analytics, and the R programming language, towards becoming a data driven practitioner, and gaining a competitive edge in the job market.
By the end of this Professional Certificate, you will be able to explain the data analyst and data scientist roles. You will work with Excel spreadsheets and utilize them for data analysis to create charts and plots. You will utilize Cognos Analytics to create interactive dashboards.
You will work with relational databases and query data using SQL statements. You will use the R programming language to complete the entire data analysis process – including data preparation, statistical analysis, data visualization, predictive modeling, and creating interactive data applications.
- Utilize Excel spreadsheets to perform a variety of data analysis tasks like data wrangling, using pivot tables, data mining, & creating charts
- Create relational databases and tables, query data, sort, filter and aggregate result sets using SQL and R from JupyterLab
- Complete the data analysis process, including data preparation, statistical analysis, predictive modeling, using R, R Studio, and Jupyter
- Communicate your data findings using various data visualization techniques including, charts, plots & interactive dashboards with Cognos and R Shiny
There are a total of 9 Courses in this IBM Data Analyst Professional Certification course. They are:
- Introduction to Data Analytics
- Excel basics for Data Analysis
- Data Visualization and Dashboards with Excel and Cognos
- Assessment for Data Analysis and Visualization foundation
- Introduction to R Programming for Data Science
- SQL for Data Science with R
- Data Analysis with R
- Data Visualization with R
- Data Science with R – Capstone Project
Best for: Beginners | Course Duration: 6 months | Provider: IBM
Info: Visit this course and get amazing offers on this course
Data Analysis and Visualization Foundations Specialization
Rating: 4.8
This Specialization prepares you for this data-driven transformation by teaching you the core principles of data analysis and visualization and by giving you the tools and hands-on practice to communicate the results of your data discoveries effectively.
You will learn the skills required to successfully start data analysis tasks by becoming familiar with spreadsheets like Excel. You will examine different data sets, load them into the spreadsheet, and employ techniques like summarization, sorting, filtering, & creating pivot tables.
This Specialization is designed for learners interested in starting a career in the field of Data or Business Analytics, as well as those in other professions, who need basic data analysis and visualization skills to supplement their primary job tasks.
- Describe the data ecosystem, tasks a Data Analyst performs, as well as skills and tools required for successful data analysis
- List various types of charts and plots and create them in Excel as well as work with Cognos Analytics to generate interactive dashboards
- Explain basic functionality of spreadsheets and utilize Excel to perform a variety of data analysis tasks like data wrangling and data mining
- Explain what Data Analytics is and the key steps in the Data Analytics process.
Best for: Beginners | Course Duration: 4months | Provider: IBM
Info: Visit this course and get amazing offers on this Course
Foundations: Data, Data, Everywhere – Google
Rating: 4.8
This is the first course in the Google Data Analytics Certificate. These courses will equip you with the skills you need to apply to introductory-level data analyst jobs. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions.
In this course, you’ll be introduced to the world of data analytics through hands-on curriculum developed by Google. The material shared covers plenty of key data analytics topics, and it’s designed to give you an overview of what’s to come in the Google Data Analytics Certificate.
Current Google data analysts will instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.
By the end of this course, you will:
- Gain an understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job.
- Learn about key analytical skills (data cleaning, data analysis, data visualization) and tools (spreadsheets, SQL, R programming, Tableau) that you can add to your professional toolbox.
- Discover a wide variety of terms and concepts relevant to the role of a junior data analyst, such as the data life cycle and the data analysis process.
- Evaluate the role of analytics in the data ecosystem.
- Conduct an analytical thinking self-assessment.
- Explore job opportunities available to you upon program completion, and learn about best practices in the job search.
Best for: Beginners | Course Duration: 22hrs | Provider: Google
Info: Visit this course and get amazing offers on this course
And here the list ends. So, these are the Best Data Analytics Courses on Coursera for Beginners to Advanced. I will keep adding more Best Data Analytics on Coursera to this list.
Conclusion
I hope these Best Data Analytics Courses on Coursera for Beginners to Advanced will definitely help you to enhance your skills. If you have any doubts or questions, feel free to ask me in the comment section.