Data Analytics Courses

Data analytics is the process of examining data and extracting actionable insights. Once the raw data is pulled together, it’s analyzed in order to draw a conclusion that’s meaningful for business execs. It’s used to reveal trends and metrics that would otherwise be lost in the mass of information.

Strong data analysis skills could get you hired in a highly rewarding field, and lead to a life-long career full of growth opportunities. If you’ve got your Excel basics down pat, we’re here to share some of the best courses that are sure to lead you to a great data analyst job.

Data Analytics Courses

Here are a few courses that you can take if you’re an aspiring data analyst:

Data Analytics Bootcamp - Thinkful

This course covers everything you need to know to start your career as a data analyst. You’ll learn all the necessary skills from qualified instructors, and you’ll continue to be supported with a 1-on-1 mentor and support team. You'll also get a data analytics certification upon completion. This course will set you up for success and guarantees a job after graduation.

This bootcamp is unique since you’ll get much more than a skills-based data analysis education. In addition to a thorough curriculum, you’ll also benefit from:

• Career coaching
• Portfolio guidance
• A data analysis capstone project

In this course, you’ll learn how to reshape data to make sense out of it. You’ll be able to catch the missing details in the data, which is considered to be the most critical part of data analysis. By the end of the course, you’ll be able to:

• Use data aggregation methods.
• Combine data sets
• Reshape data.
• Handle the missing data.

Data Analyst In Python - Dataquest

This course covers the fundamentals of Python and will provide you with an overview of Python programming. You’ll also learn to code using mobile application data, and work with different kinds of data, update variables, and manipulate Python dictionaries. This course will enable you to create your own data science project.

By the end of this course, you’ll be able to:

• Analyze different app profiles on the iOS app store.
• Understand the fundamentals of data science.
• Use Jupyter Notebook, a popular tool.
• Build a portfolio project.

Python For Data Science and AI - IBM

In this intermediate course, some key concepts of Python programming language will be covered. You’ll learn data cleansing, which is considered to be a critical skill for any data analyst or data scientist job. Essentially, you’ll learn to cleanse, standardize, and analyze messy data using Python’s DateTime module.

By the end of this course, you’ll be able to:

• Combine the skills to create a portfolio project.
• Understand object-oriented programming in Python.
• Clean messy data.
• Work with dates and times.

Pandas And NumPy Fundamentals - Dataquest

Pandas and NumPy are two popular Python open-source libraries. As the course begins, you’ll learn concepts such as vectorized operations. You’ll also learn how to select data based on its value using a method called Boolean indexing. Pandas is one of the most widely used open-source libraries for data science. After knowing the basics of Pandas and NumPy, you’ll be able to frame and filter data.

By the end of this course, you’ll be able to:

• Understand the basics of NumPy and Pandas to put data in order and analyze it.
• Understand how Pandas make data analysis easier.
• Understand how vectorized operations make working with data faster.
• Select data by value using Boolean indexing.

Storytelling Through Data Visualization storytellingwithdata.com

Graphs are one of the most effective ways to visualize data. But simple graphs don’t always suffice when it comes to representing complex datasets. This material will teach you to communicate insights from data by telling stories using data visualization. Plots like Seaborn are used to create attractive and catchy visuals and to draw appealing statistical graphics. Specialized tools like Basemap, a toolkit used for 2D graphical representations, also helps analyze data in a business context.

Data Cleaning Project Walkthrough - Dataquest

This course will walk you through each phase of data cleansing. You’ll learn the ins and outs of computer correlations in Pandas. Once completed, you’ll be able to visualize and analyze data. Ultimately, you will be asked to build your own portfolio by performing data analysis using maps and visualizations.

By the end of this course, you’ll know how to:

• Clean data
• Walk through each phase of data cleaning, which will help you implement the data cleansing skills on even the messiest data sets.

Next Steps

We hope this article has helped you gain a clear understanding of what it takes to become a data analyst, and how to get started in this high-paying tech field. Expand your research through reliable data analyst resources to make sure that this is a career you’ll love.

If you’d like any more guidance to help you launch your career as a data analyst, Thinkful’s team is here to support you and point you in the right direction.