FREE Data Analytics Certification By Microsoft and LinkedIn

FREE Data Analytics Certification By Microsoft and LinkedIn:-

Microsoft & Linkedin has launched FREE Data Analytics Certification.

  • Discover the skills needed for a career in data analysis.
  • Learn foundational concepts used in data analysis and practice using software tools for data analytics and data visualization.

Benefits:-

  • Gain a solid grounding in data analysis concepts
  • Explore data analysis software tools
  • Build data visualization skills

Course Modules:-

  1. Introduction to Career Skills in Data Analytics:-
  • Are you ready to take the first step on your journey as a data analyst? Whatever your goals, you don’t need a background in computer science to get started today.
  • In this course, instructor Robin Hunt gives you a comprehensive, behind-the-scenes look at what it’s really like to be a data analyst, from wielding data concepts and business intelligence skills, to landing your first role and advancing your career.
  • Explore the power of data and data analysis to develop a better understanding of the role.
  • Learn about business intelligence, data-driven decision-making, data collection methods, discovery, and interpretation, as well as how to structure, assess, and transform data using core functions in Excel and Power BI.
  • Gather insights from Robin on modeling, visualization, and mapping out the job market as an early-career analyst.
  • By the end of this course, you’ll have the skills you need to set out on a new career path and tackle the Microsoft GSI Data Analytics certification exam.

Skills covered:-

  • Tech Career Skills
  • Data Analytics

2) Learning Data Analytics: 1 Foundation

  • 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.

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.

Skills covered:-

  • Data Analytics

3)Learning Data Analytics Part 2: Extending and Applying Core Knowledge

  • It’s one thing to work with data. It’s another to provide quality data sets and accurate visualizations for decisions to be made.
  • 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. Robin discusses business rules, filtering out the noise in the data we all deal with, and how to deliver what decision-makers want.
  • She covers how to create data sets with queries, joins, and appends, then goes into building aggregate data with total queries.
  • Robin goes over pivots, how to use pivots to build basic dashboards and visualizations, and how to use Power Query for data transformations.
  • She concludes with best practices for meetings and taking your work to the next level for your organization.

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.

Skills covered

  • Data Analytics

FREE Data Analytics Certification By Microsoft and LinkedIn:-

Click Here To Enroll FOR FREE


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