Is IBM Data Analyst Professional Certificate on Coursera worth it? [Review]

Hello guys, if you want to become a Data Analyst in 2022 and looking for the best online resources to learn Data Analysis essentials and kick start your career then you have come to the right place. Earlier, I have shared the best Data Analysis Courses for beginners and in this article, I am going to introduce you to one of the most popular Cyber Security certifications from Coursera, IBM's Data Analyst Professional Certification. If you don't know Coursera brings the best learning material and resources from top companies like IBM and Google as the world's top universities like the Univerity of Michigan and Stanford. Their Professional certifications are also well recognized and well structured to learn in-demand tech skills and this is one of them. 

Many people think that the concept of data analytics is new. Still, actually, humans were using analytics since the 19th century, and maybe even before. Still, it got more popular in 1960 when people start using computers but nowadays are used in every company and sting are millions on the job listing websites across the globe.

Many people think that you need a university degree to get a data analyst job. Still, you can now access many different online courses to gain the skills needed for this position, but some of you will be confused about what course you should get. My advice to you is this is the IBM Data Analyst Professional Certificate program offered by IBM.

Review IBM's Data Analyst Professional Certificate on Coursera - Is it worth it?

As I have said before, whenever I join a course, I look into three main parameters, who is the instructor, how the course is structured, I mean what is covered and what is not covered, and what other people are saying about the course. Hence, I will also review this course on the above three parameters. 

1. The Instructors Review

 data analysis specialization was created by 9 professional workers in the IBM company and they are all in a great position as data scientists and data analyzers, so when you enroll in the program, you will learn from people who have solid experience in this field and all information are true compared to the other courses offered by just amateurs.

2. Course Content and Structure

This is a Professional certificate in Coursera, which means it's a collection of courses to teach you all the essential skills needed to become a Data Analyst. Let's go into teach of these courses and find out what are you going to learn. 

2.1. Introduction to Data Analytics

You will start learning what are the data analyst job and the different types of data analysts. Then, you will learn the different types of data structures and file formats and different types of data repositories like databases and warehouses. Also, you will learn how to identify, gather and import data from different sources and visualize them.

2.2. Excel Basics for Data Analysis

The excel spreadsheet is one of the most used applications for performing data analysis, and you will gain some knowledge of using this software and navigate through its options. Then you will learn to perform the basic tasks such as entering and viewing data and how to import data from different resources. Finally, some of the built-in functions are used inside the excel software.

2.3. Data Visualization and Dashboards with Excel and Cognos

This section will teach you to use excel for making data visualization like basic charts and pivot tables visualization. Then you will learn to create more advanced charts like scatter plots and histograms and learn the basics of the dashboard. Finally, you will learn to use another analytic tool called Cognos analytics and explore its options.

2.4. Python for Data Science, AI & Development

Starting with the basics of the python programming languages like data types and how to store values inside a variable and store multiple values inside one variable, known as tuples, lists, dictionaries, and sets. Later, you will see the for loops, how to iterate over items, work with files and data, and use the API and web scraping.

2.5. Python Project for Data Science

This section relies on the previous ones. You have to understand python language to demonstrate your knowledge in this language and create a program that extracts stock data using different Python libraries with Jupyter Notebook.

2.6. Databases and SQL for Data Science with Python

Learn the basics of the SQL language used to pull data from a database and explore the concepts behind databases in general and the relationships of different tables inside the database. Next, you will learn how to apply advanced queries for searching inside the database and accessing the database using the python language.

2.7. Data Analysis with Python

This is the most fun part where you will learn how to analyze data using python, which is the purpose of this whole program. Data analysis with python involves using different libraries such as NumPy for mathematical calculation, Pandas for importing and working with data, and SciPy for applying machine learning algorithms to your data.

2.8. Data Visualization with Python

Starting by learning how to use the matplotlib library to visualize data and creating different plots such as area plots, histograms, pie charts, and more. You will also see some advanced visualization such as waffle charts and how to create them and learn other Data visualization libraries like Seaborn and Folium.

2.9. IBM Data Analyst Capstone Project

This the final section will require you to apply what you’ve learned in the previous courses to solve a real-world problem using python and data analytics skills and the will assume that you have recently joined the organization and started your journey in this field so you will get areal world experience before applying to a position of a data analyst.

3. People's Review

This is the third and very important parameter to check before joining any course. When it comes to social proof, this Data Analyst Professional certificate is trusted by more than 33,870 students and it has on average 4.7 ratings which are phenomenal.  

When it comes to learner outcomes, more than 25% of people who have joined this professional certification have started a new career after completing this specialization.

In short, this is definitely a great course to join on Coursera particularly if you're interested in Data Analysis and want to become a Data Analyst, which is a great career path. It pays well and there is a lot of demand for Data Analysis experts around the world. 

Here is the link to join this professional certificate - IBM Data Analyst Professional Certificate 

That's all about the review of Coursera's most popular Data Analyst Professional Certification. Data analysis is more than just taking one course and calling yourself a data analyst. Many companies require you to have more skills than you’ve learned in this program, like statistics and using the R language for data analysis, so you have to learn more before applying for that position. It's offered by IBM, one of the top IT companies, and totally worth it. 

By the way, you can either join this professional certificate alone or you can take a Coursera Plus membership which allows access to more than 3000+ Coursera courses and unlimited access to popular Coursera certifications and specializations. If you want to take more than one course or certificate then you should join Coursera Plus. 

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Thanks for reading this article. If you like this review of Coursera and IBM's Machine Learning Specialization, then please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. - And, If you are looking for the best Udemy online courses to learn Cyber Security and Information Security,  you can also check out the Complete Cyber Security Course: Hackers Exposed! course by Nathan House on Udemy. It has a couple of parts and each one covers one essential topic for Cyber Security in great detail. It is also one of the most popular and highest-rated Udemy courses to learn Cyber Security.