Review - Is IBM Data Analytics with Excel and R Professional Certificate Worth it?

Companies are always collecting data about their customer’s behavior on their platform or maybe their products review and many other standards to make better decisions to improve their services and the user experience. Still, this data needs someone who can leverage the power of the data to make decisions, which is the role of data analysts. This career is one of the hottest in this century. Analyzing the data to get insight and better understand your users and customer will help you make your business successful or maybe have a good position in a company. 

Still, many people are wondering about the right courses to start among thousands available online. I have the best course called IBM Data Analytics with Excel and R Professional Certificate from IBM.

1. The Instructors Review

The specialization created by employees in the IBM company means you are getting the information from industry experts in data science and data analytics and not just amateurs who create a course about data analytics and don’t give you all the information needed to start a career in this field.

2. Course Content

2.1. Introduction to Data Analytics

Start  the course by defining what data analytics is, the different types of data analytics, and the role of data analysts, data engineers, and data science. Next, you will see an overview of the data analyst ecosystem and the differences between data structures, file format, and databases. 

Also, you will see how together data from different sources. Finally, learn about data mining and the career opportunities of this field.

2.2. Excel Basics for Data Analysis

Starting by learning how to use the excel spreadsheet and navigate through its options and how to perform some actions and tasks like entering and viewing data and some formulas and functions. Next, you will learn how to import data files in excel and clean data. Finally, learn how to analyze data, use some of the most useful functions, and create pivot tables.

2.3. Data Visualization and Dashboards with Excel and Cognos

You will learn the basics of charts and how to use excel software to make data visualization like creating scatter charts, treemaps, map charts, and creating a simple dashboard using excel. Later, you will explore another way to create a dashboard using Cognos Analytics and explore its advanced capabilities.

2.4. Introduction to R Programming for Data Science

You will learn the basics of the R programming language, and it is used a lot among data analysts and data science alongside python and learn the basic data types like variables, strings. You will be introduced to the RStudio. Also, learn some of the most common data structures like vectors, lists, and data frames. Finally, learn the loops functions and conditions and performing regular expression and reading data files using R language.

2.5. SQL for Data Science with R

You will learn how to use the SQL language, which is used to extract the data from the database using its queries. Next, you will learn the databases and the relation between tables inside the database, and how to create them in the cloud. Later, you will explore some of the SQL language’s intermediate functions, such as grouping data and working with multiple tables. Finally, using the R language in the database and import database files in the R language and more.

2.6. Data Analysis with R

The main use of the R language is analyzing data. First, you will start by understanding the problems that this language can solve, then move processing data using the R language, like dealing with missing values and data formatting and normalization. You will also see the descriptive statistics and grouping data in R language and explore different linear regressions and model evaluation.

2.7. Data Visualization with R

You will learn how to create data visualization by using the ggplot2 library to create different charts such as bar charts, box plots, scatter plots, and learn how to customize them. Finally, learn how to create an interactive dashboard to tell your story of the data visualization, learn its benefits, crate simple shiny apps, and deploy it.

2.8. Data Science with R — Capstone Project

This section should be taken after the previous courses and apply what you have learned in this capstone project. You will be assumed that you have joined an organization, and you have to collect and process data, make data visualization and dashboard, build R shiny dashboard app, and deploy it.

Conclusion

This specialization can be your starting point in the career of a data analyst. Still, you have to develop more skills like statistics and learn more about the R language and maybe python language to become ready for a position in the data analytics field.