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    • Big Data Analytics

    Big Data Analytics Courses Online

    Master big data analytics for processing and analyzing large datasets. Learn to use tools like Hadoop, Spark, and NoSQL databases.

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    Explore the Big Data Analytics Course Catalog

    • I

      IBM

      Generative AI: Prompt Engineering Basics

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI, OpenAI, Large Language Modeling, Image Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.3K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Data Visualization with R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Dashboard, Ggplot2, Plot (Graphics), Shiny (R Package), R Programming, Leaflet (Software), Graphing, Scatter Plots, Box Plots, Spatial Data Analysis, Histogram, UI Components, User Interface (UI)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      259 reviews

      Beginner · Course · 1 - 4 Weeks

    • N

      Northwestern University

      Organizational Leadership

      Skills you'll gain: Influencing, Persuasive Communication, Design Thinking, Data-Driven Decision-Making, Leadership, Strategic Communication, Innovation, Collaboration, Crisis Management, Negotiation, Organizational Leadership, Ideation, Team Leadership, Resource Allocation, Human Centered Design, Teamwork, Motivational Skills, Corporate Communications, Marketing Strategies, Marketing Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • C

      Coursera Project Network

      Python for Data Analysis: Pandas & NumPy

      Skills you'll gain: Pandas (Python Package), NumPy, Data Analysis, Data Science, Python Programming, Data Structures, Data Manipulation, Computer Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      333 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • 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

    • I

      IBM

      SQL: A Practical Introduction for Querying Databases

      Skills you'll gain: SQL, Relational Databases, Microsoft SQL Servers, MySQL, Query Languages, Database Systems, Databases, Database Management, Stored Procedure, IBM DB2, Data Manipulation, Data Analysis, Transaction Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      583 reviews

      Beginner · Course · 1 - 3 Months

    • S

      SAS

      SAS Programmer

      Skills you'll gain: Data Manipulation, SAS (Software), Data Access, Data Import/Export, Microsoft Excel, Data Analysis, Consolidation, Data Transformation, Requirements Analysis, Exploratory Data Analysis, Data Validation, Statistical Programming, Statistical Analysis, Data Processing, SQL, Data Presentation, Data Cleansing, Descriptive Statistics, Debugging

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.5K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Marketing in a Digital World

      Skills you'll gain: Digital Marketing, Marketing, Marketing Strategies, MarTech, Digital Advertising, Digital Transformation, 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

    • U

      University of California, Davis

      Fundamentals of GIS

      Skills you'll gain: ArcGIS, GIS Software, Spatial Data Analysis, Data Sharing, Spatial Analysis, Geographic Information Systems, Geospatial Mapping, Metadata Management, Data Quality, Data Mapping, File Management, Data Presentation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • 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

    • K

      Kennesaw State University

      Six Sigma Yellow Belt

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Lean Methodologies, Data Collection, Process Improvement, 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

    • P

      PwC

      Problem Solving with Excel

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Spreadsheet Software, Data Analysis Expressions (DAX), Data Validation, Complex Problem Solving, Statistical Analysis, Financial Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.4K reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Generative AI: Prompt Engineering Basics: IBM
    • Data Visualization with R: IBM
    • Organizational Leadership: Northwestern University
    • Python for Data Analysis: Pandas & NumPy: Coursera Project Network
    • Getting started with Google Workspace: Google Cloud
    • SQL: A Practical Introduction for Querying Databases: IBM
    • SAS Programmer: SAS
    • Marketing in a Digital World: University of Illinois Urbana-Champaign
    • Fundamentals of GIS: University of California, Davis
    • Learn to Program: The Fundamentals: University of Toronto

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Big Data Analytics

    Big data analytics refers to the application of advanced data analysis techniques to datasets that are very large, diverse (including structured and unstructured data), and often arriving in real time. The ability to process data at this scale is increasingly essential to navigating today’s business world, and it is at the core of important applications such as machine learning, business intelligence, financial engineering, and other software tools to enable data-informed decision-making.

    Computer programs have been used to assist with data analysis for decades, but tools like Microsoft Excel and traditional relational database management systems (RDBMS) queried with SQL are not capable of handling today’s high-volume, high-velocity datasets. Instead, today’s data management professionals rely on high-powered data infrastructure designed to work with distributed file systems and cloud computing resources - particularly the open-source Apache Hadoop ecosystem, including high-speed data processing with Apache Spark and distributed SQL engines like Apache Hive.‎

    Organizations of all types and sizes are seeking ways to leverage the possibilities of big data to improve operations through reduced costs and faster decision-making, create new products and services, or advance our knowledge about the world. Big data analytics skills can thus open up a wide range of career opportunities, from working as a “quant” on Wall Street to developing navigation systems for autonomous vehicles to helping to discover more effective medicines and drugs in health science.

    Two of the most broadly-applicable roles in this field are data engineers, who build the data infrastructure needed to deliver big data-scale datasets efficiently and reliably, and the data scientists responsible for analyzing them. These roles are in high demand, and are highly-paid as well; according to Glassdoor, data engineers earn an average annual salary of $102,864, and data scientists earn an average annual salary of $113,309.‎

    Absolutely! Data science is one of the most popular topics to learn about on Coursera, and there are a variety of options to build your skills in big data analytics. You can take online courses and Specializations from top-ranked schools like the University of Pennsylvania and the University of California San Diego, as well as leading companies like IBM, PwC, Cloudera, and Google Cloud. And regardless of where you choose to learn from, Coursera gives you the ability to access course materials and complete assignments on a flexible schedule, making this a great fit for students and mid-career professionals alike.‎

    Before you start learning big data analytics, it’s helpful to have an understanding of database management and the fundamentals of how programming languages work. Specifically, experience with SQL, Python, Java, or R can be useful when studying big data analytics. You also may find it beneficial to know how to work with Hadoop and Linux and use basic math and statistics. Additionally, strong analytical skills and a curiosity about playing with data come in handy when you learn big data analytics.‎

    The right people for roles in big data analytics are inquisitive problem solvers who like working with numbers and using statistics to sort through large amounts of data. They typically have work experience or coursework in high-level math or computer programming. A background in behavioral analysis can also be useful for roles in big data analytics because individuals often seek to understand or predict what influences the behavior represented by data. Big data analysts may often need soft skills, such as communication and collaboration skills they use when explaining what they see in the data and working with team members on projects.‎

    If you like working with numbers and are comfortable using statistical techniques, learning big data analytics may be right for you. The amount of data collected on a daily basis is already massive and continues to grow, so organizations need analysts who can curate and prepare data for businesses, governments, and other groups to use. Learning big data analytics may interest you if you possess strong analytical and problem-solving skills and want to apply those skills to sorting and analyzing data to find what’s useful for a client. You may be able to use the knowledge you gain to land an internship or seek a career in data science filling roles in a variety of industries.‎

    Online Big Data Analytics courses offer a convenient and flexible way to enhance your existing knowledge or learn new Big Data Analytics skills. With a wide range of Big Data Analytics classes, you can conveniently learn at your own pace to advance your Big Data Analytics career skills.‎

    When looking to enhance your workforce's skills in Big Data Analytics, 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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