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Beginner Data Analysis Courses

Beginner data analysis courses can help you learn data collection techniques, basic statistical concepts, data visualization, and interpretation of results. You can build skills in using spreadsheets for data manipulation, creating charts for visual representation, and applying descriptive statistics to summarize findings. Many courses introduce tools like Excel, Google Sheets, and data visualization software such as Tableau, showing you how to effectively analyze and present data to support decision-making.


Popular Beginner Data Analysis Courses and Certifications


  • 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

  • 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
    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 Presentation, Data Transformation, Microsoft Excel

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

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Data Analysis with Python

    Skills you'll gain: Exploratory Data Analysis, Model Evaluation, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Data Preprocessing, Regression Analysis, Data Science, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Data Visualization, NumPy, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    20K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Data Analysts' Toolbox - Excel, Power BI, Python, & Tableau

    Skills you'll gain: Data Analysis Expressions (DAX), Power BI, Pivot Tables And Charts, Microsoft Excel, R Programming, Alteryx, Dashboard, Statistical Programming, Data Transformation, Tableau Software, Data Cleansing, Data Presentation, Data Visualization Software, Interactive Data Visualization, Debugging, Data Visualization, Automation, Python Programming, Data Structures, Statistical Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    27 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Pennsylvania

    Data Analysis Using Python

    Skills you'll gain: Matplotlib, Data Analysis, Pandas (Python Package), Data Visualization, Data Science, Data Cleansing, Pivot Tables And Charts, Data Visualization Software, Data Preprocessing, Data Manipulation, Scatter Plots, NumPy, Exploratory Data Analysis, Jupyter, Data Import/Export, Histogram, Python Programming, Data Structures, Programming Principles

    4.5
    Rating, 4.5 out of 5 stars
    ·
    429 reviews

    Beginner · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • Status: Preview
    Preview
    S

    S.P. Jain Institute of Management and Research

    Data Analysis

    Skills you'll gain: Descriptive Statistics, Data Analysis, Analytics, Quantitative Research, Sampling (Statistics), Probability & Statistics, Business Analytics, Statistical Analysis, Regression Analysis, Data-Driven Decision-Making, Statistical Hypothesis Testing, Business Analysis, Microsoft Excel, Variance Analysis, Statistical Inference

    Build toward a degree

    4.5
    Rating, 4.5 out of 5 stars
    ·
    22 reviews

    Beginner · Course · 1 - 3 Months

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Analyze and Interpret Data Using Excel

    Skills you'll gain: Scatter Plots, Data Visualization, Regression Analysis, Excel Formulas, Microsoft Excel, Data Analysis, Descriptive Statistics, Data Visualization Software, Analytics, Statistical Analysis, Statistical Methods, Descriptive Analytics, Correlation Analysis, Statistics, Analysis, Exploratory Data Analysis, Pivot Tables And Charts, Trend Analysis

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    R

    Real Madrid Graduate School Universidad Europea

    Must-Know Concepts - Basic requirements for data analysis

    Skills you'll gain: Data Presentation, Matplotlib, Analytics, Probability Distribution, Data Processing, Statistical Methods, Exploratory Data Analysis, Statistical Analysis, Probability, Data Cleansing, Computer Programming Tools, Data Collection, Performance Measurement, Python Programming, Technical Analysis

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.3K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Data Analysis with Pandas and Python

    Skills you'll gain: Pandas (Python Package), Data Import/Export, Matplotlib, Pivot Tables And Charts, Jupyter, Data Visualization Software, Data Visualization, Microsoft Excel, Data Analysis, Text Mining, Data Manipulation, Data Cleansing, NumPy, Data Analysis Software, Data Wrangling, Time Series Analysis and Forecasting, Python Programming, Data Preprocessing, Data Structures, Development Environment

    4.7
    Rating, 4.7 out of 5 stars
    ·
    41 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Illinois Urbana-Champaign

    Introduction to Applied Business Analytics

    Skills you'll gain: Business Analysis, Analytics, Data Preprocessing, Data Analysis, Data-Driven Decision-Making, Data Presentation, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    311 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 beginner data analysis courses

  • Foundations: Data, Data, Everywhere: Google
  • Excel Basics for Data Analysis: IBM
  • Introduction to Data Analytics: IBM
  • Data Analysis with Python: IBM
  • Data Analysts' Toolbox - Excel, Power BI, Python, & Tableau: Packt
  • Data Analysis Using Python: University of Pennsylvania
  • Data Analysis: S.P. Jain Institute of Management and Research
  • Analyze and Interpret Data Using Excel: EDUCBA
  • Must-Know Concepts - Basic requirements for data analysis: Real Madrid Graduate School Universidad Europea
  • Introduction to Statistics: Stanford University

Frequently Asked Questions about Beginner Data Analysis

Beginner data analysis refers to the foundational skills and techniques used to interpret and analyze data. It is important because data-driven decision-making is increasingly vital in various fields, from business to healthcare. Understanding data analysis allows individuals to extract meaningful insights from raw data, enabling them to make informed decisions, identify trends, and solve problems effectively. As organizations continue to rely on data, having a grasp of beginner data analysis can empower individuals to contribute significantly to their teams and enhance their career prospects.‎

With skills in beginner data analysis, you can explore various job opportunities across multiple sectors. Common roles include data analyst, business analyst, marketing analyst, and research assistant. These positions often involve collecting, processing, and analyzing data to support decision-making processes. Additionally, industries such as finance, healthcare, and technology are increasingly seeking professionals who can interpret data effectively, making beginner data analysis a valuable skill set in today's job market.‎

To succeed in beginner data analysis, you should focus on developing several key skills. These include proficiency in spreadsheet software like Excel, basic statistical knowledge, and familiarity with data visualization tools. Additionally, understanding how to use programming languages such as Python or R can be beneficial. Learning how to clean and manipulate data, as well as interpret results, are also crucial skills that will enhance your analytical capabilities and prepare you for real-world applications.‎

There are numerous online courses available for beginner data analysis that cater to various learning styles and preferences. Some recommended options include the Data Analysis and Interpretation Specialization, which covers essential techniques and tools, and the Data Analysis with Python Specialization, which focuses on using Python for data analysis tasks. These courses provide structured learning paths and practical exercises to help you build your skills effectively.‎

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

  1. Preview the first module of many beginner data analysis 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 beginner data analysis, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn beginner data analysis, start by identifying your learning goals and preferred methods. You can enroll in online courses, watch tutorial videos, or read books on the subject. Hands-on practice is crucial, so work on real datasets to apply what you learn. Additionally, consider joining online communities or forums where you can ask questions and share insights with others. This collaborative approach can enhance your understanding and keep you motivated throughout your learning journey.‎

Typical topics covered in beginner data analysis courses include data collection methods, data cleaning and preparation, basic statistical concepts, data visualization techniques, and the use of analytical tools and software. Courses may also introduce you to programming languages like Python or R, as well as how to interpret and communicate findings effectively. By covering these essential topics, beginner data analysis courses equip you with the foundational knowledge needed to analyze data confidently.‎

For training and upskilling employees in beginner data analysis, consider courses like the Data Analysis and Visualization Foundations Specialization, which provides a comprehensive overview of data analysis techniques and visualization tools. Additionally, the Statistics and Data Analysis with Excel Specialization is ideal for those who prefer to work with Excel. These courses can help employees develop essential skills that enhance their productivity and decision-making capabilities.‎

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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