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Data Analytics Courses

Data analytics courses can help you learn data visualization, statistical analysis, and data cleaning techniques. You can build skills in interpreting complex datasets, making data-driven decisions, and communicating insights effectively. Many courses introduce tools like Excel, SQL, and Tableau, that support analyzing data and presenting findings. You'll also explore methods such as regression analysis and A/B testing, which are crucial for evaluating performance and optimizing strategies.

Popular Data Analytics Courses and Certifications

  • Status: Free Trial
    Free Trial
    I

    IBM

    Introduction to Data Analytics

    Skills you'll gain: Statistical Visualization, Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Apache Hive, Data Collection, Data Mart, Data Science, Data Warehousing, Data Visualization, Analytics, Data Cleansing, Apache Spark, Data Lakes, Data Visualization Software, Relational Databases, Microsoft Excel

    4.8
    Rating, 4.8 out of 5 stars
    ·
    20K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    G

    Google

    Google Data Analytics

    Skills you'll gain: Data Storytelling, Rmarkdown, Data Literacy, Data Visualization, Data Presentation, Data Ethics, Data Cleansing, Data Validation, Ggplot2, Tableau Software, Sampling (Statistics), Presentations, Spreadsheet Software, Data Analysis, Stakeholder Communications, LinkedIn, Data Structures, Object Oriented Programming (OOP), Interviewing Skills, Applicant Tracking Systems

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    180K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Advanced Excel Analytics, Automation & Data Analysis

    Skills you'll gain: Excel Macros, Data Validation, Scatter Plots, Pivot Tables And Charts, Microsoft Excel, Data Visualization, Regression Analysis, Excel Formulas, Histogram, Data Analysis, Data Integrity, Descriptive Statistics, Data Visualization Software, Spreadsheet Software, Analytics, Statistical Analysis, Data Analysis Expressions (DAX), Statistical Methods, Descriptive Analytics, Automation

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Excel Basics for Data Analysis

    Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Analysis, Data Import/Export, Spreadsheet Software, Data Wrangling, Data Quality, Pivot Tables And Charts, Google Sheets, Data Manipulation, Data Science, Information Privacy

    4.7
    Rating, 4.7 out of 5 stars
    ·
    11K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    I

    IBM

    IBM Data Analyst

    Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Visualization, Data Presentation, Interactive Data Visualization, Generative AI, Model Evaluation, SQL, Data Transformation, Data Analysis, Statistical Visualization, IBM Cognos Analytics, Excel Formulas, Professional Networking, Data Import/Export, Microsoft Excel, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    98K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    D

    DeepLearning.AI

    DeepLearning.AI Data Analytics

    Skills you'll gain: Data Storytelling, Web Scraping, Google Sheets, Data Visualization, Data Presentation, Spreadsheet Software, Large Language Modeling, Tableau Software, Data Literacy, Dashboard, LinkedIn, Pandas (Python Package), Time Series Analysis and Forecasting, Probability & Statistics, Extract, Transform, Load, Statistical Analysis, Statistics, Data Manipulation, Data Analysis, Descriptive Statistics

    4.8
    Rating, 4.8 out of 5 stars
    ·
    239 reviews

    Beginner · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    G

    Google

    Foundations: Data, Data, Everywhere

    Skills you'll gain: Data Ethics, Data Analysis, Analytics, Data-Driven Decision-Making, Google Sheets, Business Analytics, Spreadsheet Software, Analytical Skills, Tableau Software, Data Sharing, Data Collection, Data Cleansing, Data Processing, Data Visualization Software, Data Visualization, SQL

    4.8
    Rating, 4.8 out of 5 stars
    ·
    121K reviews

    Beginner · Course · 1 - 4 Weeks

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM Data Analytics with Excel and R

    Skills you'll gain: Data Storytelling, Data Presentation, Data Visualization, Interactive Data Visualization, Data Visualization Software, Database Design, Shiny (R Package), Dashboard, Data Wrangling, Exploratory Data Analysis, Relational Databases, Data Analysis, Statistical Visualization, Big Data, Microsoft Excel, IBM Cognos Analytics, Analytical Skills, Excel Formulas, Data Manipulation, Web Scraping

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    31K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Preview
    Preview
    S

    Simplilearn

    Data Analytics Course with Generative AI

    Skills you'll gain: Exploratory Data Analysis, Generative AI, Analytics, Data Analysis, Extract, Transform, Load, Data Integration, Interactive Data Visualization, Data Visualization, Real Time Data, Predictive Analytics, Data-Driven Decision-Making, Data Storytelling, Predictive Modeling, Forecasting, Data Transformation, Descriptive Analytics, Data Modeling, Data Quality, Risk Analysis, Model Evaluation

    4.4
    Rating, 4.4 out of 5 stars
    ·
    7 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    M

    Meta

    Introduction to Data Analytics

    Skills you'll gain: Data Storytelling, Data Presentation, Business Metrics, Key Performance Indicators (KPIs), Data Cleansing, Data Modeling, Analytics, Data Analysis, Data Visualization, Data Validation, Exploratory Data Analysis, Data Quality, Business Analysis, Data Manipulation, Generative AI, Data Collection, Data Management, Marketing

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Introduction to Data Analytics for Business

    Skills you'll gain: Data Governance, Data Management, Business Analytics, Analytics, Data Quality, Data Analysis, Business Intelligence, Big Data, Data Storage Technologies, Databases, Organizational Structure, Relational Databases, SQL, Data Storage, Cloud Computing

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.2K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Data Analytics Capstone: Complete a Case Study

    Skills you'll gain: LinkedIn, Data Analysis, Data Processing, Spreadsheet Software, Case Studies, Google Analytics, Google Sheets, Analysis, Analytical Skills, Interviewing Skills, AI Enablement, Data Storytelling, Data Visualization Software, Business Analytics, Artificial Intelligence, Data-Driven Decision-Making, Portfolio Management, Data Cleansing, Data Visualization, Presentations

    4.8
    Rating, 4.8 out of 5 stars
    ·
    19K reviews

    Beginner · Course · 1 - 4 Weeks

What brings you to Coursera today?

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In summary, here are 10 of our most popular data analytics courses

  • Introduction to Data Analytics: IBM
  • Google Data Analytics: Google
  • Advanced Excel Analytics, Automation & Data Analysis: EDUCBA
  • Excel Basics for Data Analysis: IBM
  • IBM Data Analyst: IBM
  • DeepLearning.AI Data Analytics: DeepLearning.AI
  • Foundations: Data, Data, Everywhere: Google
  • IBM Data Analytics with Excel and R: IBM
  • Data Analytics Course with Generative AI: Simplilearn
  • Introduction to Data Analytics: Meta

Frequently Asked Questions about Data Analytics

Data analytics is the process of examining data sets to draw conclusions about the information they contain. It involves using various tools and techniques to analyze data, identify patterns, and make informed decisions. In today's data-driven world, data analytics is crucial for businesses and organizations as it helps them understand customer behavior, optimize operations, and drive strategic initiatives. By leveraging data analytics, companies can enhance their competitiveness and make evidence-based decisions that lead to better outcomes.‎

A career in data analytics can open doors to various job opportunities. Common roles include data analyst, business intelligence analyst, data scientist, and data engineer. These positions often involve interpreting complex data sets, creating visualizations, and providing actionable insights to stakeholders. Additionally, industries such as finance, healthcare, marketing, and technology are increasingly seeking professionals skilled in data analytics, making it a versatile and in-demand field.‎

To succeed in data analytics, you need a combination of technical and analytical skills. Key skills include proficiency in data manipulation tools like Excel, SQL, and programming languages such as Python or R. Understanding statistical analysis, data visualization techniques, and machine learning concepts is also beneficial. Furthermore, strong problem-solving abilities and critical thinking are essential for interpreting data effectively and communicating findings to non-technical audiences.‎

There are numerous online courses available for those interested in data analytics. Some of the best options include the Google Data Analytics Professional Certificate and the IBM Data Analytics with Excel and R Professional Certificate. These programs provide comprehensive training and practical experience, making them ideal for anyone looking to build a solid foundation in data analytics.‎

Yes. You can start learning data analytics on Coursera for free in two ways:

  1. Preview the first module of many data analytics courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in data analytics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn data analytics, start by identifying your learning goals and the specific skills you want to acquire. You can begin with introductory courses that cover the basics of data analysis and gradually progress to more advanced topics. Engage with hands-on projects to apply what you learn in real-world scenarios. Additionally, joining online communities or forums can provide support and resources as you navigate your learning journey.‎

Data analytics courses typically cover a range of topics, including data collection and cleaning, exploratory data analysis, statistical methods, data visualization, and predictive modeling. Many courses also introduce tools and software commonly used in the industry, such as Excel, SQL, and programming languages like Python or R. By exploring these topics, learners can develop a well-rounded understanding of data analytics and its applications.‎

For training and upskilling employees in data analytics, programs like the Google Advanced Data Analytics Professional Certificate and the DeepLearning.AI Data Analytics Professional Certificate are excellent choices. These courses are designed to equip professionals with the necessary skills to analyze data effectively and make data-driven decisions, enhancing their contributions to their organizations.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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