Best Data Classes Online

For students who are interested in the work that data scientists do in their careers, this seminar introduces the field and how to join it. The tutorial begins with an overview of the role that Python plays in data science as an open-source programming language. Students learn about the skills and tools that data scientists use their their day-to-day work as well as how to work with data without advanced math skills. At the end of the session, students also get to see data science in action with a demonstration.

This tutorial teaches students easy techniques for optimizing their time spent in Microsoft Excel spreadsheets. Students discover keyboard shortcuts, autofill options, and ways to spend less time reformatting data and grids. Additionally, students learn to create easy charts and harness commands. By the end of the class, students will have acquired 10 new skills in Excel.

This course guides students through a practice-based curriculum designed to help them enter careers in data analytics. Students start by learning about structured thinking for data analysis and how businesses solve economic, financial, and statistical problems with data analytic solutions. By gaining skills in SQL, Python, and Tableau, students learn to analyze and visualize data and present their findings and conclusions. Students graduate with a porfolio of work, including two capstone data analytics projects.

Through this sequence of two courses, students prepare for careers in data analytics. Students begin by learning about the theory and applications of data analytics, gaining skills in using pivot tables and statistics in Excel to understand, analyze, and visualize data. Then, students dig into practicing data analysis, developing proficiency with Python, SQL, and Tableau before learning about big data, machine learning, and ethical issues in data analysis. Students complete the course with a portfolio of professional data analytics work.

These eight sequential courses prepare beginner data analysts for careers in the field. Students start by learning about data and the kinds of problems data analysis can solve, then develop skills in SQL in order to extract, store, and clean data for analysis. Students also gain experience with data visualization and programming with R for data analysis. In the final course, students develop a data analysis case study for their capstone project and benefit from lessons in job hunting before they graduate with a certificate from Google.

Students in this course track learn the essential skills of a data scientist. As they move through the course track, students learn about data management and statistical analysis, as well as how businesses make use of data insights. Students build visualizations in Power BI, Seaborn, and Tableau and develop skills for data research, deep learning, and machine learning. A final exam testing their new knowledge helps students earn a digital badge.

In this series of four courses, beginner students gain all the tools that advanced business professionals use in Microsoft Excel. Students learn how to navigate and customize spreadsheets and get experience solving problems with formulas and functions before discovering automation techniques for working with large data sets. In addition, students learn to use graphs, charts, pivot tables and charts, and macros for data analysis and gain familiarity with Visual Basic for Excel. Graduates earn a professional certificate.

Through this bootcamp, students with experience in programming and statistics can jumpstart their careers in data science. Students learn to use Python, SQL, Pandas, and APIs for data science as they develop skills for data wrangling and data analysis. In addition, students gain experience with inferential statistics, machine learning, deep learning, and natural language processing as they advance through the course and begin to scale up their work. By the end of the course, students will have produced two capstone projects.

Advanced programmers prepare for careers in data engineering through this course. Students learn advanced applications of Python and gain experience with Apache Airflow and Spark, Docker, and Kubernetes. Students start by working with big data sets and cloud computing, then advance to working with containers and APIs before learning about data modeling and warehousing. The curriculum is practice-oriented, and students complete the course with a portfolio of professional work, including two capstone projects.

Students in this course level up from novice to expert in using Microsoft Excel for business. Students learn the fundamentals of using data in spreadsheets, including data integrity, as they learn how to create charts and graphs and take advantage of conditional formatting and templates. As students progress through the course, they gain experience with functions, formulas, macros, and pivot tables and pivot charts, and also learn to use automated tools and do data analysis. At the end of the course, graduates earn an Excel certification from Austin Peay State University continuing education, recognized by the global CPD Certification Service.

Through a series of three courses, beginners in this professional certificate program gain advanced skills in Microsoft Excel. Students start by learning how Excel can power business data analysis and discover how to create and manage spreadsheets, enter and manage data, and generate charts for data visualization. Then, students learn to use functions, formulas, tables, and pivot tables and charts before gaining experience with automation, macros, and Visual Basic for Excel. Graduates earn a professional certificate through edX.

Offered through University of California San Diego Extension, this course prepares advanced programmers for careers in machine learning. Students start with learning about and analyzing data, before moving into machine learning algorithms and deep learning. Students gain hands-on experience developing machine learning platforms and have the option of specializing in advanced deep learning, image processing, or natural language processing with additional study. Career coaching is integrated into the course curriculum, and students produce a machine learning capstone project for their professional portfolio.