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If you're looking to get into data analytics, chances are you've already reviewed several data analyst job postings. You've probably also seen several programming tools and languages listed in the required skill set: SQL, Excel, Power BI, Tableau, Python, and more.
Well, you can enroll in several courses to learn each of these skills. But wouldn't it be much better if you could progress through a comprehensive boot camp that would help you learn all of these skills and also build a portfolio of projects?
the completely free Data Analyst Bootcamp for Beginners by Alex the Analyst is what you are looking for to launch your career as a data analyst. In addition to learning SQL, Excel, Power BI, Tableau, and Python, you'll also create projects, learn how to write your resume, and much more. Now let's go directly to the content of this bootcamp.
Link: Data Analyst Bootcamp for Beginners (SQL, Tableau, Power BI, Python, Excel, Pandas, Projects, more)
The course first begins with a general roadmap on how to become a data analyst and then proceeds to cover each of the tools needed in great detail, the first being SQL.
This SQL section of the tutorial is divided into three parts: Basics, Intermediate SQL, and Advanced SQL.
The Basic SQL section covers:
- Select + From statements
- where statement
- Group by and sort by
The intermediate SQL portion of the tutorial covers the following:
- Interior and exterior joints
- Unions
- Statement of the case
- have clause
- Update and delete data
- alias
- Partition by
The Advanced SQL section will teach you:
- Common Table Expressions (CTEs)
- temporary tables
- String functions
- Stored Procedures
- Subqueries
The module concludes with a couple of portfolio projects on data exploration and cleansing using SQL.
As a data analyst, it shouldn't surprise you that all your work involves wrangling numbers in spreadsheets. After mastering the fundamentals of SQL, which he can improve with practice, she will begin learning Excel.
Almost every organization uses Excel or a similar spreadsheet tool, so learning how to work with them is very useful.
The Excel section covers the following topics:
- Dynamic tables
- Formulas
- xLOOKUP
- Conditional format
- Graphics
- Cleaning data
As with the SQL section, you will be able to work on a complete project on data analysis using Excel.
Now that you've mastered SQL and Excel, which should be enough for almost all basic data analysis, it's time to move on to learning about BI tools.
The Tableau tutorial section begins with installing Tableau and covers the following topics:
- Creating your first visualization
- Use calculated fields and containers
- Using unions
Then you'll work on a beginner-friendly project.
The Power BI section guides you through using Microsoft Power BI for data analysis and visualization, starting with installing Power BI.
Below is an overview of what this section covers:
- Creating your first visualization
- Using power query
- Create and manage relationships
- Use DAX in Power BI
- Using drill down
- Conditional formatting and lists.
- Popular visualizations in Power BI
Like the previous sections, you'll also be able to work on a guided project in this section of Power BI.
Now that you are familiar with most of the tools used in data analysis, it is time to learn the most used data programming language. What is Python?
This section covers Python and data analysis with Pandas, with the opportunity to work on simple projects. Topics covered include: Python Basics, which includes the fundamentals of Python and a couple of projects to apply what you've learned. Then you will learn web scraping with Python.
The pandas tutorial covers the following topics:
- Reading files
- Filter columns and rows
- Indices
- Grouped and aggregated functions
- Merge data frames
- Creating visualizations with pandas
- Data Cleaning
- Exploratory Data Analysis (EDA)
You will then be able to work on two portfolio projects on how to work with APIs and web scraping.
At this point, you've learned all the skills you need to become a data analyst and have also worked on projects to add to your portfolio. What's next? It's about applying for jobs, interviewing, and getting that job.
The final section of the data analyst bootcamp offers useful career tips for navigating the job search process:
- How to create a portfolio website
- How to Create Good Data Analyst Resumes
- Tips on How to Use LinkedIn to Get a Job
This is really helpful as very few courses cover this aspect of what you need to do. after You have learned the necessary skills and construction projects.
I hope you found this full review of this bootcamp helpful. So, what are you waiting for? Go ahead and start learning today.
Happy learning and coding!
Bala Priya C. is a developer and technical writer from India. He enjoys working at the intersection of mathematics, programming, data science, and content creation. His areas of interest and expertise include DevOps, data science, and natural language processing. He likes to read, write, code and drink coffee! Currently, he is working to learn and share his knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more.
