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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

    • Status: Free
      Free
      U

      University of Toronto

      Learn to Program: The Fundamentals

      Skills you'll gain: Programming Principles, Debugging, Software Documentation, Python Programming, Computer Programming, Program Development, Integrated Development Environments, Data Structures, File Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.7K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Marketing in a Digital World

      Skills you'll gain: Digital Marketing, Marketing, Marketing Strategies, MarTech, Digital Transformation, Digital Advertising, E-Commerce, Price Negotiation, Consumer Behaviour, Product Development, Product Promotion, Innovation, Customer Engagement

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      17K reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Getting started with Google Workspace

      Skills you'll gain: Google Docs, Gmail, Google Sheets, Google Workspace, Presentations, Calendar Management, Spreadsheet Software, File Management, Excel Formulas, Email Security, Data Visualization, Productivity Software, Collaborative Software, Excel Macros, Data Validation, Document Management, Setting Appointments, Meeting Facilitation, Sales Presentations, Version Control

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University at Buffalo

      Digital Manufacturing & Design Technology

      Skills you'll gain: Model Based Systems Engineering, Systems Engineering, Product Lifecycle Management, Intrusion Detection and Prevention, Security Controls, Performance Measurement, Control Systems, Continuous Monitoring, Anomaly Detection, Machine Controls, Incident Response, Digital Transformation, Vulnerability Assessments, Process Analysis, Data Sharing, Manufacturing Processes, Manufacturing Operations, Product Design, Manufacturing and Production, Constructive Feedback

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Generative AI: Introduction and Applications

      Skills you'll gain: Generative AI, ChatGPT, OpenAI, Prompt Engineering, Large Language Modeling, Artificial Intelligence, Program Development, Content Creation, Image Analysis, Virtual Environment

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      W

      West Virginia University

      Forensic Accounting and Fraud Examination

      Skills you'll gain: Auditing, Loss Prevention, Internal Controls, Financial Controls, Threat Detection, Anomaly Detection, Financial Auditing, Cybersecurity, Financial Data, Cyber Operations, Investigation, Criminal Investigation and Forensics, Analytics, Specialized Accounting, Cyber Attacks, Security Awareness, Big Data, Accounting, Business Ethics, Compliance Reporting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.1K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of California, Davis

      GIS Data Formats, Design and Quality

      Skills you'll gain: Spatial Data Analysis, Spatial Analysis, ArcGIS, Geographic Information Systems, Geospatial Mapping, Data Quality, Data Mapping, Data Modeling, Data Storage, Data Sharing, Data Manipulation, Relational Databases, Query Languages

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.1K reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Convolutional Neural Networks in TensorFlow

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Computer Vision, Image Analysis, Applied Machine Learning, Deep Learning, Artificial Neural Networks, Supervised Learning, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      8.2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Maryland, College Park

      Digital Transformation with Data Analytics Projects

      Skills you'll gain: Digital Transformation, Business Transformation, Data Strategy, Agile Methodology, Analytics, Business Analytics, Leadership, Business Process Reengineering, Business Modeling, Business Strategy, Strategic Thinking, Competitive Analysis, Market Opportunities, Project Management

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Data Science Challenge

      Skills you'll gain: Applied Machine Learning, Jupyter, Machine Learning Algorithms, Machine Learning, Predictive Modeling, Data Science, Python Programming, Predictive Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      161 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • K

      Kennesaw State University

      Six Sigma Yellow Belt

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Lean Methodologies, Process Improvement, Data Collection, Quality Improvement, Process Optimization, Lean Six Sigma, Correlation Analysis, Statistical Hypothesis Testing, Kaizen Methodology, Process Analysis, Probability Distribution, Regression Analysis, Process Capability, Business Process, Statistical Process Controls, Quality Management, Team Management, Continuous Improvement Process

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California San Diego

      Introduction to Discrete Mathematics for Computer Science

      Skills you'll gain: Graph Theory, Logical Reasoning, Combinatorics, Computational Logic, Deductive Reasoning, Cryptography, Probability, Key Management, Computational Thinking, Encryption, Network Analysis, Public Key Cryptography Standards (PKCS), Algorithms, Theoretical Computer Science, Python Programming, Data Structures, Cybersecurity, Arithmetic, Computer Programming, Mathematical Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.6K reviews

      Beginner · Specialization · 3 - 6 Months

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

    • Learn to Program: The Fundamentals: University of Toronto
    • Marketing in a Digital World: University of Illinois Urbana-Champaign
    • Getting started with Google Workspace: Google Cloud
    • Digital Manufacturing & Design Technology: University at Buffalo
    • Generative AI: Introduction and Applications: IBM
    • Forensic Accounting and Fraud Examination: West Virginia University
    • GIS Data Formats, Design and Quality: University of California, Davis
    • Convolutional Neural Networks in TensorFlow: DeepLearning.AI
    • Digital Transformation with Data Analytics Projects: University of Maryland, College Park
    • Data Science Challenge: Coursera Project Network

    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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