Grow With Google Data Analytics

The Best Grow With Google Data Analytics Course In 2022

The FREE course from Grow with Google on Data Analytics!!!

Hey coding enthusiasts it’s a great time to start learning Data Analytics with Google. Yes, you heard it right Google is providing a FREE course on Data Analytics on the Coursera platform where anyone can access absolutely free.

Basically, starting your Data Analytics with Grow with Google is one of the best options for a beginner or intermediate level coder to learn data analytics concepts or you can enhance your skills set and boost your hirability through innovative, independent learning.

 This course will give you a comprehensive understanding of what data analytics is all about and how it can be applied to different domains. 

In this blog, we will go through what you’ll learn, course overview, syllabus, eligibility criteria, Prerequisites and Requirements, and how you can access this course for FREE.

Let’s get started

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What is Data Analytics?

Data Analytics

The term “Data Analytics” is often said to be one of the most important skills for tomorrow’s workforce, but what exactly is it?

Data analytics is the process of examining data and putting it into a meaningful context. Data analytics has become increasingly important in recent years as companies find new ways to collect, store, analyze, and use data.

It has become an integral part of many different fields including marketing, business intelligence, education, healthcare, and more. With so much information available at our fingertips, understanding how to use this data can be extremely valuable to us.

Data Analytics Course Overview Through Grow with Google

Data Analytics Course Overview Through Grow with Google

The course starts off by introducing you to the world of data analytics through practical examples before diving deep into each aspect of the industry’s jargon-filled landscape.

You will learn techniques for collecting structured and unstructured data; tools for transforming raw data into insights; popular algorithms for statistical analysis; how to apply machine learning, natural language processing (NLP), sentiment analysis, and more; as well as best practices in communicating your findings to.

What You Will Learn

  1. Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job.
  2. Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming.
  3. Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau).
  4. Learn how to visualize and present data findings in dashboards, presentations and commonly used visualization platforms.

MEDIUM OF INSTRUCTIONS: English.

MODE OF DELIVERY: Video and Text-based.

COURSE COST: FREE.

TIMELINE: Approximately 6 months.

SKILL LEVEL: Beginner.

CERTIFICATE AFTER COMPLETION: YES.

Syllabus of Data Anaylytics Course

Following are the 8 syllabus you will learn in this course:

Syllabus 1: Foundations: Data, Data, Everywhere

By the end of this course, you will: –

  1. Gain an understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job.
  2. Learn about key analytical skills (data cleaning, data analysis, data visualization) and tools (spreadsheets, SQL, R programming, Tableau) that you can add to your professional toolbox.
  3. Discover a wide variety of terms and concepts relevant to the role of a junior data analyst, such as the data life cycle and the data analysis process.
  4. Evaluate the role of analytics in the data ecosystem.
  5. Conduct an analytical thinking self-assessment.
  6. Explore job opportunities available to you upon program completion, and learn about best practices in the job search.

Syllabus 2: Ask Questions to Make Data-Driven Decisions

By the end of this course, you will:

  1. Learn about effective questioning techniques that can help guide analysis.
  2. Gain an understanding of data-driven decision-making and how data analysts present findings.
  3. Explore a variety of real-world business scenarios to support an understanding of questioning and decision-making.
  4. Discover how and why spreadsheets are an important tool for data analysts.
  5. Examine the key ideas associated with structured thinking and how they can help analysts better understand problems and develop solutions.
  6. Learn strategies for managing the expectations of stakeholders while establishing clear communication with a data analytics team to achieve business objectives.

Syllabus 3: Prepare Data for Exploration.

By the end of this course, you will:

  1. Find out how analysts decide which data to collect for analysis.
  2. Learn about structured and unstructured data, data types, and data formats.
  3. Discover how to identify different types of bias in data to help ensure data credibility.
  4. Explore how analysts use spreadsheets and SQL with databases and data sets.
  5. Examine open data and the relationship between and importance of data ethics and data privacy.
  6. Gain an understanding of how to access databases and extract, filter, and sort the data they contain.
  7. Learn the best practices for organizing data and keeping it secure.

Syllabus 4: Process Data from Dirty to Clean.

By the end of this course, you will be able to do the following:

  1. Learn how to check for data integrity.
  2. Discover data cleaning techniques using spreadsheets.
  3. Develop basic SQL queries for use on databases.
  4. Apply basic SQL functions for cleaning and transforming data.
  5. Gain an understanding of how to verify the results of cleaning data.
  6. Explore the elements and importance of data cleaning reports.

Syllabus 5: Analyze Data to Answer Questions.

By the end of this course, you will:

  1. Learn how to organize data for analysis.
  2. Discover the processes for formatting and adjusting data.
  3. Gain an understanding of how to aggregate data in spreadsheets and by using SQL.
  4. Use formulas and functions in spreadsheets for data calculations.
  5. Learn how to complete calculations using SQL queries.

Syllabus 6: Share Data Through the Art of Visualization.

By the end of this course, you will:

  1. Examine the importance of data visualization.
  2. Learn how to form a compelling narrative through data stories.
  3. Gain an understanding of how to use Tableau to create dashboards and dashboard filters.
  4. Discover how to use Tableau to create effective visualizations.
  5. Explore the principles and practices involved with effective presentations.
  6. Learn how to consider potential limitations associated with the data in your presentations.
  7. Understand how to apply best practices to a Q&A with your audience.

Syllabus 7: Data Analysis with R Programming.

By the end of this course, you will:

  1. Examine the benefits of using the R programming language.
  2. Discover how to use RStudio to apply R to your analysis.
  3. Explore the fundamental concepts associated with programming in R.
  4. Explore the contents and components of R packages including the Tidyverse package.
  5. Gain an understanding of data frames and their use in R.
  6. Discover the options for generating visualizations in R.
  7. Learn about R Markdown for documenting R programming.

Syllabus 8: Google Data Analytics Capstone: Complete a Case Study.

By the end of this course, you will:

  1. Learn the benefits and uses of case studies and portfolios in the job search.
  2. Explore real-world job interview scenarios and common interview questions.
  3. Discover how case studies can be a part of the job interview process.
  4. Examine and consider different case study scenarios.
  5. Have the chance to complete your own case study for your portfolio.

Eligibility Criteria

Basically, if anyone wants to apply for Data Analytics with Grow with Google no need for any prior experience or degree anyone can apply for the course.

How to apply

To apply for DSA with Grow with Google: Click here.

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