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Beginner Data Analysis Courses Online

Learn beginner data analysis techniques using tools like Excel and Python. Understand how to clean, analyze, and visualize data for insights.

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Explore the Beginner Data Analysis Course Catalog

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Pearson

    Data Science Fundamentals, Part 1

    Skills you'll gain: Extract, Transform, Load, Data Validation, Data Transformation, Applied Machine Learning, Object-Relational Mapping, Data Wrangling, Data Cleansing, Data Manipulation, Data Integration, Web Scraping, Data Quality, Data Pipelines, Pandas (Python Package), Descriptive Statistics, Data Modeling, Data Science, Python Programming, Scikit Learn (Machine Learning Library), Extensible Markup Language (XML), Data Analysis

    Beginner · Specialization · 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, Data Integrity, Information Privacy

    4.8
    Rating, 4.8 out of 5 stars
    ·
    10K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Introduction to Data Analytics

    Skills you'll gain: Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Data Wrangling, Apache Hive, Data Collection, Data Mart, Data Science, Data Warehousing, Data Visualization, Analytics, Data Cleansing, Apache Spark, Data Lakes, Data Visualization Software, 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, Data Wrangling, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Regression Analysis, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Feature Engineering, Data Visualization, Data Pipelines, NumPy, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    19K reviews

    Intermediate · Course · 1 - 3 Months

  • 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
    ·
    118K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    S

    S.P. Jain Institute of Management and Research

    Data Analysis

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

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    18 reviews

    Beginner · Course · 1 - 3 Months

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  • 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
    ·
    4.2K reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    M

    Macquarie University

    Statistics and Data Analysis with Excel

    Skills you'll gain: Interactive Data Visualization, Pivot Tables And Charts, Data Visualization, Data Presentation, Data-Driven Decision-Making, Microsoft Excel, Correlation Analysis, Forecasting, Regression Analysis, Excel Formulas, Statistics, Statistical Hypothesis Testing, Descriptive Statistics, Data Analysis, Business Analytics, Statistical Inference, Box Plots, Statistical Analysis, Statistical Modeling, Statistical Visualization

    5
    Rating, 5 out of 5 stars
    ·
    23 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    Logistic Regression Fundamentals: Analyze & Predict

    Skills you'll gain: SAS (Software), Predictive Modeling, Regression Analysis, Analytics, Statistical Methods, Data Transformation, Statistical Analysis, Business Analytics, Logistics, Estimation, Probability

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Data Analysis with R

    Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Analysis, R Programming, Data Manipulation, Data Visualization, Predictive Analytics, Statistical Analysis, Data Science, Regression Analysis, Predictive Modeling, Statistical Modeling, Feature Engineering, Machine Learning Methods

    4.7
    Rating, 4.7 out of 5 stars
    ·
    338 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    M

    Meta

    Python Data Analytics

    Skills you'll gain: Pandas (Python Package), Data Analysis, Exploratory Data Analysis, Data Modeling, Data Manipulation, Jupyter, Matplotlib, Data Visualization, Programming Principles, Data Cleansing, Data Visualization Software, Python Programming, Scripting, Scripting Languages

    4.3
    Rating, 4.3 out of 5 stars
    ·
    231 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Assessment for Data Analysis and Visualization Foundations

    Skills you'll gain: Data Mining, Dashboard, Data Collection, Microsoft Excel, Data Quality, Data Cleansing, Data Analysis, Data Visualization Software, IBM Cognos Analytics, Exploratory Data Analysis, Pivot Tables And Charts, Data Wrangling

    4.6
    Rating, 4.6 out of 5 stars
    ·
    312 reviews

    Beginner · Course · 1 - 4 Weeks

Beginner Data Analysis learners also search

Beginner Data Analysis
Data Analysis
Beginner Data Science
Analysis
R
Beginner Data Analytics
Beginner R Programming
Data
1234…834

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

  • Data Science Fundamentals, Part 1: Pearson
  • Excel Basics for Data Analysis: IBM
  • Introduction to Data Analytics: IBM
  • Data Analysis with Python: IBM
  • Foundations: Data, Data, Everywhere: Google
  • Data Analysis: S.P. Jain Institute of Management and Research
  • Introduction to Statistics: Stanford University
  • Statistics and Data Analysis with Excel: Macquarie University
  • Logistic Regression Fundamentals: Analyze & Predict: EDUCBA
  • Data Analysis with R: IBM

Frequently Asked Questions about Beginner Data Analysis

Beginner data analysis is a foundational level course or skill that focuses on teaching individuals how to collect, clean, organize, interpret, and visualize data. It introduces learners to key concepts and techniques in data analysis, such as data exploration, data manipulation, and basic statistical analysis. Throughout the course, individuals will gain hands-on experience with popular data analysis tools and software, such as Excel or Python, and learn how to apply these tools to real-world datasets. By mastering beginner data analysis, learners can develop the necessary skills to understand and draw insights from data, laying a strong foundation for more advanced data analysis techniques and applications.‎

To begin your journey in Data Analysis, there are several key skills that you should focus on learning:

  1. Mathematics and Statistics: A solid understanding of mathematical concepts such as algebra, probability, and calculus is essential for data analysis. Additionally, knowledge of statistics, including descriptive and inferential statistics, will help you analyze and interpret data accurately.

  2. Programming Language: Learning a programming language like Python or R is crucial for data analysis. These languages offer various libraries and tools that simplify data manipulation, analysis, and visualization.

  3. SQL: SQL (Structured Query Language) is commonly used for querying and managing large datasets in databases. Familiarity with SQL will enable you to retrieve, filter, and aggregate data efficiently.

  4. Data Visualization: As a data analyst, you need to be able to communicate your findings effectively. Learning data visualization tools like Tableau, Power BI, or Matplotlib will help you create visually appealing and insightful graphs, charts, and dashboards.

  5. Excel: Proficiency in Microsoft Excel is essential for data manipulation, analysis, and reporting. Understanding functions, pivot tables, and data cleaning techniques in Excel will prove beneficial throughout your data analysis journey.

  6. Data Cleaning and Preprocessing: Real-world datasets are often messy and incomplete. Acquiring skills in data cleaning and preprocessing techniques will enable you to handle missing data, remove outliers, and transform data into a usable format for analysis.

  7. Critical Thinking and Problem-Solving: Data analysis requires logical reasoning and the ability to think critically. Developing analytical thinking skills will help you ask the right questions, solve complex problems, and draw meaningful insights from data.

Remember, data analysis is a continuous learning process, so remaining curious, adaptable, and committed to building your knowledge base will facilitate your growth in this field.‎

With Beginner Data Analysis skills, you can start exploring entry-level roles such as Data Analyst, Junior Data Scientist, Business Intelligence Analyst, Data Engineer, and Market Research Analyst. These roles will allow you to gain practical experience in collecting, cleaning, analyzing, and presenting data, providing valuable insights to decision-makers in various industries. As you continue to develop your skills, you can progress to more advanced positions and specialize in areas such as data visualization, machine learning, or predictive analytics.‎

Beginner Data Analysis is best suited for individuals who have a strong interest in working with data and are curious about uncovering insights and patterns. This course is ideal for those who enjoy problem-solving, critical thinking, and have a basic understanding of mathematics. Additionally, individuals who are detail-oriented, have good analytical skills, and are comfortable with technology will excel in studying Beginner Data Analysis.‎

Here are some topics related to Beginner Data Analysis that you can study:

  1. Introduction to Data Analysis
  2. Statistics for Data Analysis
  3. Data Visualization
  4. Data Cleaning and Preprocessing
  5. Exploratory Data Analysis
  6. Introduction to Python/R for Data Analysis
  7. SQL for Data Analysis
  8. Introduction to Machine Learning for Data Analysis
  9. Data Analysis in Excel
  10. Introduction to Tableau for Data Analysis

These topics will provide you with a strong foundation in the field of Beginner Data Analysis and equip you with the necessary skills to perform data analysis tasks effectively.‎

Online Beginner Data Analysis courses offer a convenient and flexible way to enhance your knowledge or learn new Beginner data analysis is a foundational level course or skill that focuses on teaching individuals how to collect, clean, organize, interpret, and visualize data. It introduces learners to key concepts and techniques in data analysis, such as data exploration, data manipulation, and basic statistical analysis. Throughout the course, individuals will gain hands-on experience with popular data analysis tools and software, such as Excel or Python, and learn how to apply these tools to real-world datasets. By mastering beginner data analysis, learners can develop the necessary skills to understand and draw insights from data, laying a strong foundation for more advanced data analysis techniques and applications. skills. Choose from a wide range of Beginner Data Analysis courses offered by top universities and industry leaders tailored to various skill levels.‎

When looking to enhance your workforce's skills in Beginner Data Analysis, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

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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