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    • Data Analytics

    Data Analytics Courses

    Data analytics courses can help you learn how to collect, interpret, and visualize data to uncover insights and support decision-making across industries.

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    Find the Best Data Analytics Course for Your Goals

    • U

      Unilever

      Using Data Analytics in Supply Chain

      Skills you'll gain: Data Governance, Data Storytelling, Presentations, Data Management, Supply Chain Management, Data Analysis, Data Visualization Software, Data Quality, Analytical Skills, Data Cleansing, Data Collection, Spreadsheet Software, Data Validation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      66 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California San Diego

      Data Structures

      Skills you'll gain: Data Structures, Algorithms, Data Storage, Programming Principles, Computer Programming, C++ (Programming Language), Theoretical Computer Science, File Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.5K reviews

      Intermediate · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      A Crash Course in Data Science

      Skills you'll gain: Data Science, Data Management, Data-Driven Decision-Making, Project Design, Performance Metric, Software Engineering, Machine Learning, Predictive Modeling, Statistical Inference

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • D
      S

      Multiple educators

      Machine Learning

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), Artificial Intelligence, NumPy, Predictive Modeling, Deep Learning, Reinforcement Learning, Random Forest Algorithm, Feature Engineering

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      33K reviews

      Beginner · Specialization · 1 - 3 Months

    • D

      Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • F

      Fractal Analytics

      Data Analysis Using SQL

      Skills you'll gain: Database Design, Data Manipulation, SQL, Relational Databases, Database Management, Data Analysis, Data Cleansing, Databases, Query Languages, Data Transformation, Data Integrity

      4.4
      Rating, 4.4 out of 5 stars
      ·
      41 reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      IBM & Darden Digital Strategy

      Skills you'll gain: Strategic Thinking, Digital Transformation, Business Strategy, Cloud Computing Architecture, Competitive Analysis, Cloud Services, Large Language Modeling, Business Transformation, Cloud Security, Cloud Infrastructure, Big Data, Cloud Platforms, Data Analysis, Statistical Analysis, Cloud Computing, Artificial Intelligence, Generative AI, Data Ethics, Product Lifecycle Management, Business Technologies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      45K reviews

      Beginner · Specialization · 3 - 6 Months

    • E

      Emory University

      Foundations of Marketing Analytics

      Skills you'll gain: Pivot Tables And Charts, Customer Analysis, Probability Distribution, Customer Demand Planning, Marketing Analytics, Forecasting, Descriptive Statistics, Microsoft Excel, Social Media Marketing, Exploratory Data Analysis, Probability, Statistical Analysis, Marketing Effectiveness, Target Market, Social Media, Revenue Forecasting, Time Series Analysis and Forecasting, Predictive Modeling, Statistics, Marketing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      516 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Accounting Data Analytics with Python

      Skills you'll gain: Jupyter, Matplotlib, Pandas (Python Package), Data Manipulation, SQL, Data Visualization Software, Seaborn, Data Processing, Data Structures, NumPy, Programming Principles, Business Analysis, Databases, Accounting, Relational Databases, Data Modeling, Python Programming, Descriptive Statistics, Statistical Machine Learning, Regression Analysis

      Build toward a degree

      4.4
      Rating, 4.4 out of 5 stars
      ·
      106 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Michigan

      Data Analytics in the Public Sector with R

      Skills you'll gain: Exploratory Data Analysis, Data Visualization, Plot (Graphics), Statistical Analysis, Data Presentation, Ggplot2, Program Evaluation, Policy Analysis, Surveys, Data Ethics, Data Analysis, Tidyverse (R Package), Statistical Visualization, R Programming, Statistical Methods, Data Visualization Software, Statistical Hypothesis Testing, Demography, Political Sciences, Public Policies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      73 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      E

      Edureka

      Applied Data Analytics with Python and SQL

      Skills you'll gain: Web Scraping, SQL, Pandas (Python Package), Database Management, Databases, Microsoft SQL Servers, Data Manipulation, Data Literacy, Data Analysis, NumPy, Data Visualization Software, Data Processing, Data Cleansing, Programming Principles, Python Programming, Scripting, Scripting Languages

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Virginia

      Product Analytics and AI

      Skills you'll gain: Customer Analysis, Analytics, Business Analytics, Usability Testing, Product Management, Customer Insights, A/B Testing, Product Development, Agile Methodology, User Experience, Advanced Analytics, Data-Driven Decision-Making, Data Science, Product Testing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      479 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Using Data Analytics in Supply Chain: Unilever
    • Data Structures: University of California San Diego
    • A Crash Course in Data Science: Johns Hopkins University
    • Machine Learning: DeepLearning.AI
    • Data Analysis with R: Duke University
    • Data Analysis Using SQL: Fractal Analytics
    • IBM & Darden Digital Strategy: IBM
    • Foundations of Marketing Analytics: Emory University
    • Accounting Data Analytics with Python: University of Illinois Urbana-Champaign
    • Data Analytics in the Public Sector with R: University of Michigan

    Why Learn Data Analytics?

    Data analytics is the process of examining raw data to find trends, patterns, and actionable insights. It’s a key driver in business, healthcare, finance, and technology, helping organizations make informed decisions. Learning data analytics can equip you with tools for solving problems, measuring outcomes, and creating value in a data-driven world.

    Frequently Asked Questions about Data Analytics

    Coursera’s Data Analytics courses equip learners with a broad array of analytical skills:

    • Basics of data collection, cleaning, and preprocessing
    • Techniques for statistical analysis and interpretation of data
    • Use of analytics tools and software like Python, R, SQL, and Excel
    • Data visualization skills for communicating insights effectively
    • Understanding of machine learning models for data-driven predictions
    • Application of analytics in real-world business scenarios‎

    Data Analytics courses on Coursera are designed to welcome learners at all levels:

    • Beginners without prior experience can start with introductory courses on the fundamentals of data handling and analysis.
    • Intermediate learners can build on existing knowledge with courses on specific tools or techniques.
    • Advanced users can refine their skills and learn to manage complex analytics projects and data sets.‎

    Learners completing Data Analytics courses on Coursera can earn credentials that may enhance their professional profiles:

    • Professional certificates that may indicate proficiency in various analytics tools and methodologies
    • Specializations that explore specific aspects of data analytics, from data visualization to advanced statistical methods
    • Certificates that can be seen by employers as a testament to your commitment to developing analytics skills‎

    Acquiring skills from Data Analytics courses can open doors to diverse career paths across sectors:

    • Data Analyst, turning data into insights that inform business decisions
    • Business Intelligence Analyst, developing actionable intelligence from complex datasets
    • Data Scientist, using advanced statistical techniques and machine learning to solve problems
    • Marketing Analyst, analyzing consumer data to drive marketing strategies
    • Operations Analyst, improving efficiency through data-driven process optimizations ‎

    Yes, Coursera offers a variety of free courses across many topics, including data analytics. While you can access most course materials for free by auditing the courses, this does not include graded assignments or a completion certificate. For those looking to obtain a certificate to showcase their learning or enhance their professional profile, Coursera provides the option to purchase the course. Additionally, Coursera offers free trials or financial aid to learners who qualify, making certifications more accessible to everyone.‎

    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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