IBM Data Analyst Professional Certificate Highlights:
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11 Months (3 hours weekly) of effort required
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Language: English
If you have an interest in becoming a data analyst and develop all the skills relevant to Python, excel, SQL, and more. Then this specialization is what you need to consider. Through the courses available in this specialization, you will get a chance to learn to use spreadsheets effectively. With that, you will also learn to create various charts and plots in Excel and work with IBM Cognos analytics for building dashboards. Similarly, you will also understand what data ecosystem is and how to use SQL and python from Jupyter notebooks and more.
You can also checkout IBM AI Engineering Professional Certificate Review .
IBM Data Analyst Professional Certificate (9 Courses)
There are 9 courses in this specialization.
Course 1: Introduction to data analytics (★★★★★ 4.8 | 1307 ratings | 288 reviews)
In this course, you will get an introduction to the different concepts of data analysis in detail. You will be understanding the role of a data analyst and all the tools that can be used to perform daily functions.
Course 2: Excel Basis for Data Analysis (★★★★★ 4.7 | 480 ratings | 82 reviews)
A course that has been designed to provide you with basic knowledge as to how excel spreadsheets can be used for data analysis. The course covers some of the basic steps with spreadsheets and their use in the process of analyzing data.
Course 3: Data Visualization and Dashboards with Excel and Cognos (★★★★★ 4.7 | 260 ratings | 46 reviews)
Similarly, in this course, you will understand the steps involved in the development of data visualizations using spreadsheets and dashboards.
Course 4: Python for Data Science, AI, and Development (★★★★★ 4.6 | 20,146 ratings | 3,202 reviews)
The aim of this course is to take you from zero to advanced level programming in Python in just a matter of hours. You don’t need to have any prior experience in programming to learn from this course. So, enroll today and learn python fundamentals including data structures and data analysis.
Course 5: Python Project for Data Science (★★★☆☆ 3.0 | 18 ratings | 8 reviews)
This mini-course targets all those people who want to understand the foundational Python skills required for working with data. In this course, you will get to develop a simple dashboard using Python.
Course 6: Databases and SQL for Data Science with Python (★★★★★ 4.7 | 12,789 ratings | 1,485 reviews)
This course is going to introduce you to the relational database concepts and make you understand and apply foundational knowledge of the SQL language. With that, you will also get started with performing SQL access in a data science environment. Check out Tableau online training by certified professionals.
Course 7: Data Analysis with Python (★★★★★ 4.7 | 12,920 ratings | 1,888 reviews)
If you wish to learn to analyze data using Python, then this course is what you need to enroll in. The course will take you from the basics of Python to exploring the different types of data. Similarly, you will also learn to prepare data for analysis and also perform simple statistical analysis.
Course 8: Data Visualization with Python (★★★★★ 4.5 | 8,862 ratings | 1,263 reviews)
In this engaging course, you will understand how to tell compelling stories in a step-by-step guide. The instructor will talk about how to leverage a software tool for visualizing data and also enable you to extract information in detail.
Course 9: IBM Data Analyst Capstone Project (★★★★★ 4.7 | 72 ratings | 8 reviews)
In this last course, you will learn to apply various data analytics skills and techniques that you have learned in the previous courses. Visit here to learn all about professional data engineer certification.
Reviews:
I took the first course from the specialization and found it very informational. And I think all those people who want to pursue a career in data-driven roles can easily learn a lot from this course. The course can easily give learners a holistic view of the data-driven world as a beginner (Usama T, ★★★★★).
The design of the second course was very interactive and I believe a person who even has no experience in this field can understand and execute the program very effectively. Thus this was one of the best online courses I have ever taken as it improved my understanding of data analytics. (Bongurala G, ★★★★★).
After completing the third course from the specialization, I realized that I have accomplished the most with this course. The course was very cleanly accelerated but left enough open to exploring more capabilities. Indeed the course was worth the effort (Mary AP, ★★★★★).
The third course helped me improve my visualization skills with Excel and it also introduced me to a powerful tool like IBM Cognos Analytics. I’d like to thank the instructor for this amazingly informational course (Hichem DM, ★★★★★).
The Python for data science and AI course is very suitable for all those people who don’t know anything about Python. The course has information that is easy-to-understand, to-the-point, and very engaging. The course just starts with the basics and focuses on data structures which were very interesting. Thus if you even know any programming language, this course would be a fun journey for you then (Pranay C, ★★★★★).
The fifth course from the specialization might be hard for first-time learners but I believe if one pays attention to the content of the course then he can learn a lot from it (Eddie CL, ★★★★☆).
The data analysis with Python was a very engaging course. The practice lab assignments were quite challenging but helped a lot in reinforcing my learning. And I think this course is the best one in the series so far (Tejas P, ★★★★★).
The sixth course in the specialization depicts a great review of an important topic. And if I knew how much this course could matter for the advanced capstone course then I would have paid more attention from the start. Anyways the course was a success (Daniel T, 5 stars).
I have taken almost all the courses from the specialization and believe that all these courses are worth enrolling in. The best course for me was data visualization with Python. I really connected with the format of the course. The labs were quite interesting and helped me explore different options and play around with the code in different ways (Stephen P, ★★★★★).
The last course which was a capstone project was the most engaging course according to me. The instructions in the course were clear and to-the-point, and very engaging (Clarence EY, ★★★★★).
Final Thoughts:
If you have an interest in becoming a data analyst professional or need guidance relevant to this field, then the courses in this specialization can be of great help to you.
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