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List of Free Data Analytics Certification Courses by Linkedin Learning

List of Free Data Analytics Certification Courses by Linkedin Learning

Hey everyone,This post contains list of free data analytics courses with certificates.With these courses and skills gained you will land up on your dream Job and become a Data Analyst .

Data analysts examine information using data analysis tools and help their teams develop insights and business strategies.You’ll need skills in math, statistics, communications, and working with tools designed to do data analytics and data visualization.

You will gain Top in-demand skills like Data analysis, analytics, visualization; Microsoft Excel, SQL, BI, Tableau and lot more in Data Analytics
Here are 10+ free courses for learning data analytics with more than 36 hours of content and you can also get a free certificate after completing each of these courses.

COURSE 1 : Learning Data Analytics: 1 Foundations

Level: Beginner

Duration: 3.5 hours

Learning objectives

  • Recognize the skills of a data analyst.
  • Apply SQL statements using the correct syntax.
  • Interpret existing data.
  • Explain how data is cleaned.
  • Demonstrate how to use joins.
  • Identify different types of data.
  • Describe how to model data

In this course, instructor Robin Hunt brings you into the mind of an analyst. She defines and explains foundational concepts, such as how to think about data, how to work with others in different roles to get the data you need, and the tools you need to work with data, such as Excel and Microsoft Access. She introduces you to SQL queries, PowerBI, and more. Robin goes into syntax and explains how to interpret the data you see, find the data you need, and clean the data for effective data work. She explains data governance and how to ask the right questions of different departments to gather the data you need. Robin shows how to work with data, including how to import data, work with flat files such as CSVs, and create datasets for others. Robin goes into what cleaning and modeling mean, as well as how to use Power Query in Excel. She has also added challenge/solution sets in each chapter to help you evaluate your skills.

COURSE 2 : Data Fluency: Exploring and Describing Data (2019)

Level: Beginner

Duration: 4h 19m hours

Learning objectives

  • The ROI of data fluency
  • Data ethics
  • Preparing data
  • Assessing the quality of data
  • Visualizing data with bar, pie, and line charts
  • Describing variability with the variance and standard deviation
  • Describing associations with correlations

In this course, join Barton Poulson as he focuses on the fundamentals of data fluency, or the ability to work with data to extract insights and determine your next steps. Barton shows how exploring data with graphs and describing data with statistics can help you reach your goals and make better decisions. Instead of focusing on particular tools, he concentrates on general procedures that can help you solve specific problems. Find out how to prepare data, explore it visually, and use statistical methods to describe it.

COURSE 3 : Excel Statistics Essential Training: 1

Level: Beginner + Intermediate

Duration: 3h 37m

In this course, join Barton Poulson as he focuses on the fundamentals of data fluency, or the ability to work with data to extract insights and determine your next steps. Barton shows how exploring data with graphs and describing data with statistics can help you reach your goals and make better decisions. Instead of focusing on particular tools, he concentrates on general procedures that can help you solve specific problems. Find out how to prepare data, explore it visually, and use statistical methods to describe it.

Learning objectives

  • Explain how to calculate simple probability.
  • Review the Excel statistical formulas for finding mean, median, and mode.
  • Differentiate statistical nomenclature when calculating variance.
  • Identify components when graphing frequency polygons.
  • Explain how t-distributions operate.
  • Describe the process of determining a chi-square.

COURSE 4 : Learning Excel: Data Analysis

Duration : 3h 37m

Level: Beginner + Intermediate

Learning objectives

  • Distinguish between the mean, median, and mode.
  • Describe the relationship between variance and standard deviation.
  • Identify a nondirectional hypothesis.
  • Point out the difference between COVARIANCE.P and COVARIANCE.S.
  • Explain correlation.
  • Analyze Bayes’ rule

COURSE 5 :Learning Data Visualization

In this course, Bill Shander shows how to understand your data and your audience, craft the story you need to tell, and determine the best visual model and details to use for that story.

Learning objectives

  • Describe the process by which individuals’ interests are incorporated into data visualizations.
  • Differentiate the use of the Ws in data visualization.
  • Explain techniques involved in defining your narrative when visualizing data.
  • Identify the factors that make data visualizations relatable to an audience’s interests and needs.
  • Review the appropriate use of charts in data visualizations.
  • Define the process involved in applying interactivity to data visualizations.

COURSE 6 :Power BI Essential Training

In this course, Gini von Courter helps you get started with this powerful toolset. Gini begins by covering the web-based Power BI service, explaining how to import data, create visualizations, and arrange those visualizations into reports.

Learning objectives

  • Apply the required hardware to successfully run Power BI.
  • Distinguish between different data types in Power BI.
  • Correlate the similarities between visualizations in Power BI.
  • Identify the outcomes when changes are made within Power BI and Power BI Desktop.
  • Differentiate between dashboards and reports within Power BI.
  • Determine user roles within a workspace in Power BI.
  • Manage workspaces and tools within the Power BI mobile application.

COURSE 7 : Tableau Essential Training

n this course, learn how to analyze and display data using Tableau 2021—and make better, more data-driven decisions for your company. Instructor Curt Frye shows how to install Tableau, connect to data sources, and sort and filter your data.

Learning objectives

  • Explain where a user would navigate to seek specific help in Tableau.
  • Determine the best approach for using Excel in Tableau.
  • Interpret how to use the features and functions of Tableau when creating charts.
  • Describe how best to manage data in a worksheet or visualization.
  • Explain how to create a selection filter for certain values.
  • Explain how to manage data for different chart formats.

COURSE 8 : The Non-Technical Skills of Effective Data Scientists

This course was designed to help you learn these, and other, nontechnical skills that can help you convert your first data science job into a successful, lifelong career.

Learning objectives

  • Describe the inherent ambiguity in data science projects.
  • Define cognitive empathy and how it can be acquired.
  • Differentiate the roles of skepticism, curiosity, persuasion, and diplomacy in professional data science.
  • List appropriate activities for continuing professional development.
  • Describe common interactions between scientists and senior executives.
  • Describe when it is appropriate to limit detail in discussions.

COURSE 9 : Learning Data Analytics Part 2: Extending and Applying Core Knowledge

If you are considering a course emphasis or a career in data analytics, this course can help you get off to a good start. Robin Hunt, CEO and co-founder of ThinkData Solutions, shares practical skills to help you get the most from your data and jumpstart your career in data.

Learning objectives

  • Explore concepts relating to data analytics.
  • Explain the use of wildcard characters in building queries.
  • Review types of data visualizations.
  • Describe how slicers are used.
  • Define terminology used in creating visualizations.
  • Differentiate between duplicate and reference data sets.
  • Identify licensing and permissions considerations.

COURSE 10 : Predictive Analytics Essential Training: Data Mining

This course provides several “big picture” insights, via instructor Keith McCormick, a veteran practitioner who has completed dozens of real-world projects. Keith begins by introducing you to key definitions and processes that you will need to complete the course successfully.

COURSE 11: SQL: Data Reporting and Analysis (2019)

In this course, learn how to get the data you want by writing a bit of SQL code. You won’t just be able to pull data out of the database; you’ll be able to manipulate it: merging it, grouping it, and relabeling it to get just the report you want

Learning objectives

  • Retrieving data with SELECT statements
  • Filtering and sorting your results
  • Transforming results with built-in SQL functions
  • Grouping SQL results
  • Merging data from multiple tables
  • Using variables, functions, and procedures

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