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Google Data Science Courses – Syllabus, Features, And More

Are you looking for Google Data Science Course but not sure which Institute to enroll in? Don’t worry, we have got you! Data Science is extracting meaningful insights from the pool of data for business. These data are essential and help businesses to grow. In today’s time there is an ocean of data available online, but finding the right data is a task that can only be performed by Data Science experts. Data Science offers a wide range of job opportunities to individuals.

GOOGLE DATA SCIENCE COURSES-compressed (1)

What is a Data Science?

Data Science is a field that involves the knowledge gained from structured and unstructured data. It is a combined technique from various fields. Organizations need a skilled data analyst to help them make important decisions for their company’s growth. It is a process of analyzing raw data to pull out useful insights for the companies and to derive more businesses for them. From the vast pool of data finding out the important and useful one is the role of a data analyst. The benefits of data science are to uncover hidden trends patterns, trends and valuable insights to make informed decisions.

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The Importance of Data Science Are:

Data Collection: Data Collection is a process of gathering relevant data from various sources.

Data Cleaning: The process of fixing and removing unwanted is known

as data cleaning.

Data Exploration Analysis: To better understand the nature of data through visualization and statistical methods is known as Data Exploration Analysis.

Data Visualization: Representation of data through maps.

Domain Expertise: Understanding the specific industry for the usage of information Required Skills in Data Science:

To excel in data science, individuals need diverse skills especially

designed courses for the knowledge required:

Collaboration:

  • To collaborate with various teams to work in an interdisciplinary team

Machine Learning:

  • Minimal errors and high-level skills for the cogunstruction of predictive models
  • Understanding data modelling, machine learning algorithms and computing is crucial for machine learning experts

Statistical Knowledge:

  • Understanding the statistical concepts for data analysis and modelling
  • Knowledge of probability, testing and regression analysis is beneficial

What is Google Data Science?

Google Data Science is a complete suite of data management, analytics and machine learning tools to generate insights and unlock value from data.

Who is a Data Scientist?

A Data Scientist is a professional who processes the collected data and uses them to compel stories to inform business decision-making. By using the data they explain the phenomena happening around them to help organisations. They use machine learning to classify data to make predictions related to models. A minimum of an undergraduate degree in data science or related field is required to become a Data Science professional.

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What are the Job Role of a Data Scientist?

  • Data Engineer: The key responsibility of the Data Engineer is to generate and analyse the tools.
  • Business Intelligence Analyst: Business analyst helps companies in important decision-making.
  • Data Architect Science: Data processing is useful to design and create data systems.
  • Statistician: To interpret data is an essential job role of a statistician.
  • Quantitative Analyst: To solve the risk management problems mathematical strategies and skills are used.
  • Organizations play a crucial role as Data Science consultants: The usage of data science for business needs is fulfilled by these organizations.
  • Product Manager: The data product manager’s crucial job responsibility is to conceptualize products for the organization.
  • Data Science Trainer: The techniques and concepts of data science are taught in this educational institute.
  • Data Scientist in the Healthcare industry: Details of patients, their medicines and other medical history can be found and can be saved for future reference through data science techniques in the healthcare industry.

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What is the Role of Data Science in Google?

In Google Data Science Course, Data Science plays a major role in the world of data analytics. In this role, any candidate will work with engineers, product managers sales associates and the marketing team to adjust Google’s practice and as a Data scientist, you will evaluate and improve Google products and not only find the problem but also get to find a solution to the problem.

Top Google Data Science Course:

Below is the list of a few Google Data Science Courses:

Coursera:

Coursera is known for delivering world-class courses through an online platform method where a candidate gets the proper guidance on a chosen subject necessary for their career growth.

At Coursera, candidates will be given the Google Data Analytics Professional Certificate. This is a career path for those who are looking to have a career in Google Data Science Course. In this program, you’ll learn in-demand skills that will have you job-ready in 6 months. Candidates will not required to have any experience or degree.

Google Data Analytics Professional Certificate:

What You Will Learn:

  • Gain an immersive understanding of the practices and the processes used by a junior or associate data analyst in their day-to-day job.
  • Understand how to clean and organise data for analysis, and complete analysis and calculations using spreadsheets, SQL and R Programming.
  • Different ways how to use analytical skills like data cleaning, analysis & visualization and tools like spreadsheets, SQL, and R Programming.
  • Learn how to visualise and present data findings in dashboards, presentations and commonly used visualization platforms.

Skills You Will Learn:

  • Data Analysis
  • Creating Case Studies
  • Data Visualisation
  • Data Cleansing
  • Data Collection
  • Developing a Portfolio
  • Spreadsheet
  • Metadata
  • SQL
  • Data Ethics
  • Data Aggregation
  • Data Calculation
  • R Markdown
  • R Programming
  • RStudio
  • Tableau Software
  • Presentation
  • Data Integrity
  • Sample Size Determination
  • Decision Making
  • Problem-Solving
  • Questioning

How to Prepare for a Career in Data Analytics:

  • Receive personal-level training from Google
  • Demonstrate your proficiency in portfolio-ready projects
  • Certificate from Google
  • Qualify for in-demand in-demand job titles: Data Analyst, Junior Data Analyst, Associate Data Analyst.

The Syllabus Covered in This Course Are:

Foundations: Data, Data, Everywhere (Course 1 for 24 Hours)

  • Define and explain key concepts involved in data analytics including data analytics, and data ecosystems
  • Conduct an analytical thinking assessment giving specific examples of the application of analytical thinking
  • Describe the role of a data analyst and the job opportunities

Skills You Will Learn:

  • Spreadsheet
  • Data Integrity
  • Sample Size Determination
  • SQL
  • Data Cleansing

Ask Questions To Make Data-Driven Decisions: Course 2 for 21 Hours

What You Will Learn:

  • Explain how the problem-solving road map applies to typical analysis scenarios
  • Discuss the use of data to help in making decision
  • Demonstrate the use of spreadsheets to complete basic tasks of the data analyst including entering and organising data
  • Describe the ideas associated with thinking

Skills You Will Gain:

  • Data Analysis
  • Creating Case Studies
  • Data Visualization
  • Data Cleansing
  • Developing a Portfolio

Prepare Data for Exploration: Course 3 for 25 Hours

  • Explain what factors to consider when making decisions about data collections
  • Discuss the difference between biased and unbiased data
  • Describe the database with its references to its functions and components
  • Describe best practices for organizing data

Skills You Will Gain:

  • Decision-making
  • Spreadsheet
  • Data Analysis
  • Problem-Solving
  • Questioning

Process Data from Dirty to Clean: Course 4 for 26 Hours

What You Will Learn:

  • Define different types of data integrity and identify risks to data integrity.
  • Apply basic SQL functions to clean string variables in the database.
  • Develop queries for the use of databases.
  • Describe the process of verifying data cleaning results.

Skills You Will Gain:

  • Data Analysis
  • R Markdown
  • Data Visualization
  • R Programming
  • RStudio

Analyse Data to Answer Questions: Course 5 for 32 Hours

What You Will Learn:

Importance of organizing by using sorts and filters to analyse

Convert and format data.

Apply the use of syntax and functions to create SQL queries to combine data from multiple the database tables.

Skills you will learn:

  • Data Aggregation
  • Spreadsheet
  • Data Analysis
  • Data Calculations
  • SQL

Share Data Through the Art of Visualization: Course 6 for 25 Hours

What you will learn:

  • Describe the use of data visualization to talk about data and the results of data analysis.
  • Visualization of data tools and understanding.
  • Explain what data-driven stories are including their reference to their importance and their attributes.
  • Principles and practices with effective presentations.

Skills you will learn:

  • Data Collection
  • Spreadsheet
  • Metadata
  • SQL
  • Data Ethics

Data Analysis with R Programming: Course 7 for 36 Hours

What you will learn:

  • R Programming language and its programming
  • Generating visualizations in R Programming.
  • Understand the basics of formatting in R Markdown and emphasize content.

Skills you will learn:

  • Data Analysis
  • Tableau Software
  • Data Visualization
  • Presentation

Google Data Analytics Capstone: Complete a Case Study: Course 8 for 11 Hours

What You Will Learn:

  • Differentiate between a capstone project, a case study, and a portfolio.
  • Identify the important features of the case study.
  • Data analysis is used to process a given set of data.
  • Discuss the use of case studies or portfolios when communicating with recruiters and potential employers.

The Skills You Will Gain

  • Spreadsheet
  • Data analysis
  • SQL
  • Data Visualization
  • Data Cleansing

Course Details: Beginners Level

Course Time: 6 Months at 10 Hours a Week with Flexible Schedule

Foundations Of Data Science:

It is an advanced-level course for which no prior experience is required. It is a course for 26 hours.

Courses You Will Learn in This Topics:

  • Industries that use advanced data analytics for career opportunities
  • Explain how data professionals preserve data privacy and ethics
  • Roles and responsibilities of team members for developing project plans

The Following Skills Will Be Learnt by the Candidates:

  • Project Management
  • Sharing Insights with Stakeholders
  • Cross-functional team dynamics
  • Asking effective questions
  • Effective written communication

Ways How a Candidate Can Become an Expert as a Data Analyst:

  • After enrolling for this course, candidates will also be enrolled in this professional certificate.
  • Learn new concepts from industry experts.
  • Gain a foundational understanding.
  • Skills with hands-on projects.

There Are 5 Modules in This Course:

This course is designed in a way to help develop skills required for Google Advance Data Analytics professional roles, entry-level data scientists or advanced roles. This course will be delivered by Google employees who are currently working in the field to guide the students through hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work and helping the candidates enhance their Data Science skills.

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Introduction to Data Science Concepts: Module 1 for 4 hours

Candidates will begin with an introduction to the Google Advanced Analytics Certificate. Then you will explore the history of data science and ways that data science will help solve problems.

What’s Included in This Module-

7 Videos

  • 2 quizzes
  • 10 readings
  • 3 discussion prompts
  • 3 plugins
  • Introduction to Course 1
  • Welcome to Module 1
  • Explore your data toolbox
  • Wrap- up
  • Navigate your data career with curiosity
  • Prepare for your first assessment

10 readings

  • Google Advanced Certificate Overview
  • Course 1 Overview
  • Helpful resources and tips
  • Data discourse over the years
  • Understand your readiness score
  • Participate in program surveys
  • Engage with other learners
  • Connect with other learners
  • Glossary terms from Module 1

2 Quizzes

  • Module 1 challenge
  • Assess your readiness for the Google Advanced Data Analytics certificate

3 discussion Prompts

  • Connect with your classmates
  • Share your data experience
  • Share your experience

3 Plugins

  • Commit to completing the program
  • Your advanced data analytics certificate roadmap
  • Google advanced data analytics certificate

The Impact of Data Today: Module 2 for 4 Hours

After becoming familiar with data science, candidates are ready to explore the data career space. Here the candidates will learn about how data science professionals manage and analyse their data as well as how data-driven insights can help organizations.

What’s Included in This Course:

  • 8 Videos
  • 9 readings
  • 5 Quizzes
  • 3 discussion prompts
  • 1 plugin

8 Videos

  • Welcome to Module 2
  • Create a data-driven business solution
  • Data-driven business careers drive modern business
  • Leverage data analysis in non-profits
  • The top skills needed for a data career
  • Important data ethical considerations for data professionals
  • The data professional career space
  • Wrap up

9 Readings:

  • Profiles of data professionals
  • Difference for the future through data
  • Ideal qualities for data analytics professionals
  • Positive impact through volunteer data skills
  • Critical data security and privacy principles
  • Build the perfect data team
  • Organize your data team
  • Glossary terms from Module 2

5 Quizzes:

  • Module 2 challenge
  • Test your knowledge- data-driven careers
  • Test your knowledge- data career skills
  • Activity: organize your data team
  • Test your knowledge- work in the field

3 discussion prompts:

  • Identify local organizations that may benefit from data analytics
  • Identify your data professional strengths
  • Identify your ideal data professional role

1 Plugin:

Explore the data career neighbourhood

Your Career as a Data Professional:

As Data Science professionals you will be able to identify the skills and analyse the useful data. You will also explore how data professionals explore collaborate with teammates.

What’s Included:

  • 9 Videos
  • 6 Readings
  • 3 Quizzes

9 Videos:

  • Welcome to Module 3
  • A lifelong love of data
  • The future of data careers
  • Advice for job seekers
  • Build a professional online presence
  • Strengthen professional relationships
  • Prepare for your job search
  • Highlight both technical and people skills

6 readings:

  • Current and future tools
  • How data professionals use AI
  • The places you will go
  • Make the most out of mentorships
  • Prepare for the interview
  • Glossary terms from the module 3

3 quizzes:

  • Module 3 Challenge
  • Write prompts for Bard
  • Test your knowledge: The trajectory of the field

Data applications and workflow:

Candidates will learn about the PACE (plan, analyse, construct, execute) project workflow and how to organise a data project. You will also learn how to communicate effectively with teammates and stakeholders.

What’s Included in This Course:

  • 7 Videos
  • 9 readings
  • 6 quizzes
  • 1 discussion prompt
  • 1 plugin

7 Videos:

  • Welcome to Module 4
  • Importance of communication in a data science career
  • Introduction to PACE
  • Key elements of communication
  • Communication drives PACE
  • Connect PACE with upcoming course themes

9 Readings:

  • The PACE Stages
  • Best communication practices for data professionals
  • Communicate with stakeholders in different roles
  • Elements of successful communications
  • The value of the PACE strategy documents
  • Communicate objectives with a project proposal
  • Connect PACE with executive summaries
  • Create a project proposal
  • Glossary terms for module 4

 6 Quizzes:

  • Module 4 challenge
  • Test your knowledge- the data project workflow
  • Communicate with stakeholders within different roles
  • Test your knowledge- Elements of communication
  • Create a project proposal
  • Test your knowledge- communicate like a data professional

1 Discussion Prompt:

  • Recall a past project through PACE

1 Plugin:

Categorize: PACE workflow task

End of Course Project:

As a student, you will gain the opportunity to apply your new data, skills knowledge and practice in solving a new problem to solve a business problem.

What’s Included in This:

  • 4 Videos
  • 10 readings
  • 4 Quizzes
  • 2 Discussion Prompts

4 Videos:

  • The value of a portfolio
  • Introduction to your course 1 end-of-course portfolio project
  • End of course project wrap-up and tips for ongoing career success

10 Readings:

  • End, of course, portfolio project introduction
  • Explore your course 1 workplace scenarios
  • End of course portfolio project overview: Automatidata
  • Create your course 1 Automatidata project
  • End of course portfolio project overview: Waze
  • Create your Course 1 Waze Project

4 Quizzes:

  • Assess your course 1- end of course project
  • Create your course 1- Waze project

2 Discussions Prompt:

  • Reflect on your course 1 project
  • Course 1 learning journey

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FAQs

1.   What is the role of Data Science in Google?

The role of Data Science in Google is to identify the problem and as a Data Scientist evaluate and improve Google’s product.

2.   Is the Google Data Science Course worth it?

Google Data Science Course is a great introduction to the world of Data Science. After completing the course candidates will get certificates which will help in getting access to some career goals.

3.   What is the qualification for the Google Data Science Course?

 Qualifications required for the Google Data Science Course are a Master’s degree in a quantitative discipline, like Computer science, Maths, Statistics and Engineering.

Conclusions 

Google Data Science Course helps the candidate develop the skills required for professional roles such as entry-level and advanced-level Data Scientist roles. By the end of the course, the candidate will be able to describe the functions of data analytics and data science within an organization and identify tools used by data professionals. How to explore the value of data-based roles in organizations and investigate career opportunities for a data professional. How to explain a data project workflow and develop effective communication skills are also covered in the Google Data Science Course. However, it would be advisable for the students to do their research properly before applying for any of the above-mentioned courses.


 

 

Author:
I am skilled at researching any topic requested and values creating unique yet compelling articles for my clients. My passion for writing content and blogs has motivated me to pursue a career in content writing from IIM Skills. Before this, I have 6+ years of experience in the Banking and Media Industry with EiPi Media, Hindustan Times(Shine.com), Royal Bank of Scotland and Citibank.

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