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    • Beginner Data Analysis

    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: Free Trial
      Free Trial
      I

      IBM

      Introduction to Data Analytics

      Skills you'll gain: Data Storytelling, Data Visualization, Extract, Transform, Load, Data Analysis, Statistical Analysis, Big Data, Data Wrangling, Data Processing, Data Mining, Analytics, Data Warehousing, Data Science, Data Cleansing, Data Lakes, Data Collection, Relational Databases, Microsoft Excel

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

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Excel Basics for Data Analysis

      Skills you'll gain: Data Cleansing, Excel Formulas, Data Quality, Data Analysis, Business Analytics, Microsoft Excel, Analytical Skills, Data Manipulation, Spreadsheet Software, Pivot Tables And Charts, Data Entry, 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
      Status: AI skills
      AI skills
      G

      Google

      Google Data Analytics

      Skills you'll gain: Data Presentation, Data Storytelling, Data Cleansing, Data Visualization, Data Validation, Rmarkdown, Data Integrity, Interactive Data Visualization, Data Ethics, Dashboard, Ggplot2, Data Quality, Stakeholder Communications, Data Literacy, Data Visualization Software, Data Analysis, SQL, Interviewing Skills, Analytical Skills, Applicant Tracking Systems

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      172K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis with Python

      Skills you'll gain: Data Wrangling, Predictive Modeling, Exploratory Data Analysis, Data Manipulation, Data Import/Export, Statistical Modeling, Data Analysis, Data Visualization, Regression Analysis, Visualization (Computer Graphics), Predictive Analytics, Data Cleansing, Correlation Analysis, Statistical Analysis, Pandas (Python Package), Machine Learning Methods, Descriptive Statistics, Python Programming

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

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Jupyter, Web Scraping, Python Programming, Data Collection, Object Oriented Programming (OOP), Pandas (Python Package), Programming Principles, Data Structures, NumPy, Data Processing, Data Manipulation, Application Programming Interface (API), Data Import/Export, Computer Programming, Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      42K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations: Data, Data, Everywhere

      Skills you'll gain: Data Ethics, Data Analysis, Data-Driven Decision-Making, Data Literacy, Analytics, Spreadsheet Software, Business Analytics, Data Cleansing, Exploratory Data Analysis, Data Collection, Data Processing, Query Languages, Data Visualization Software, Data Visualization, SQL

      4.8
      Rating, 4.8 out of 5 stars
      ·
      116K reviews

      Beginner · Course · 1 - 4 Weeks

    What brings you to Coursera today?

    • Status: Preview
      Preview
      S

      Stanford University

      Introduction to Statistics

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

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.2K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Preview
      Preview
      S

      S.P. Jain Institute of Management and Research

      Data Analysis

      Skills you'll gain: Descriptive Statistics, Data Analysis, Sampling (Statistics), Business Analytics, Statistical Analysis, Statistical Hypothesis Testing, Quantitative Research, Business Mathematics, Regression Analysis, Statistical Methods, Trend Analysis, Correlation Analysis, Microsoft Excel, Statistical Inference, Exploratory Data Analysis, Variance Analysis, Probability

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      16 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: Data Storytelling, Data Visualization, Data Wrangling, SQL, Extract, Transform, Load, Pivot Tables And Charts, Matplotlib, Exploratory Data Analysis, Predictive Modeling, Relational Databases, Data Analysis, Data Visualization Software, Data Cleansing, Data Ethics, Dashboard, Jupyter, IBM Cognos Analytics, Microsoft Excel, Python Programming, Interviewing Skills

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      94K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Davis

      Learn SQL Basics for Data Science

      Skills you'll gain: Apache Spark, Data Governance, SQL, Presentations, Databricks, Data Quality, Data Pipelines, Data Storytelling, Distributed Computing, Data Presentation, Data Analysis, Big Data, Data Import/Export, Data Science, Exploratory Data Analysis, Data Modeling, Database Design, Descriptive Statistics, Data Visualization, Query Languages

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis and Visualization Foundations

      Skills you'll gain: Data Storytelling, Data Visualization, Dashboard, Extract, Transform, Load, Pivot Tables And Charts, Data Analysis, IBM Cognos Analytics, Data Cleansing, Excel Formulas, Statistical Analysis, Data Visualization Software, Looker (Software), Data Quality, Business Analytics, Big Data, Microsoft Excel, Data Wrangling, Data Processing, Data Mining, Exploratory Data Analysis

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Databases and SQL for Data Science with Python

      Skills you'll gain: SQL, Relational Databases, Stored Procedure, Database Design, Databases, Database Management, Data Analysis, Data Manipulation, Pandas (Python Package), Transaction Processing, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      22K reviews

      Beginner · Course · 1 - 3 Months

    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

    • Introduction to Data Analytics: IBM
    • Excel Basics for Data Analysis: IBM
    • Google Data Analytics: Google
    • Data Analysis with Python: IBM
    • Python for Data Science, AI & Development: IBM
    • Foundations: Data, Data, Everywhere: Google
    • Introduction to Statistics: Stanford University
    • Data Analysis: S.P. Jain Institute of Management and Research
    • IBM Data Analyst: IBM
    • Learn SQL Basics for Data Science: University of California, Davis

    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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