Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate

 

What you'll learn

Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud.

Employ BigQuery to carry out interactive data analysis.

Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.

Choose between different data processing products on Google Cloud.

Join Free: Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate 

Professional Certificate - 6 course series

Google Cloud Professional Data Engineer certification was ranked #1 

on Global Knowledge's list of 15 top-paying certifications in 2021

! Enroll now to prepare!

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87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career and provides training to support your preparation for the industry-recognized

 Google Cloud Professional Data Engineer

 certification.

Here's what you have to do

1) Complete the Coursera Data Engineering Professional Certificate

2) Review other recommended resources for the Google Cloud Professional Data Engineer certification

 exam

3) Review the Professional Data Engineer exam guide

4) Complete Professional Data Engineer sample questions

5)Register for the Google Cloud certification exam (remotely or at a test center)

Applied Learning Project

This professional certificate incorporates hands-on labs using Qwiklabs platform.These hands on components will let you apply the skills you learn. Projects incorporate Google Cloud Platform products used within Qwiklabs. You will gain practical hands-on experience with the concepts explained throughout the modules.

Applied Learning Project

 This Professional Certificate incorporates hands-on labs using our Qwiklabs platform.

These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google BigQuery, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.

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The Power of Statistics

 

What you'll learn

Explore and summarize a dataset 

Use probability distributions to model data

Conduct a hypothesis test to identify insights about data

Perform statistical analyses using Python 

Join Free: The Power of Statistics

There are 6 modules in this course

This is the fourth of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll discover how data professionals use statistics to analyze data and gain important insights. You'll explore key concepts such as descriptive and inferential statistics, probability, sampling, confidence intervals, and hypothesis testing. You'll also learn how to use Python for statistical analysis and practice communicating your findings like a data professional. 

Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. 

Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.   

By the end of this course, you will:

-Describe the use of statistics in data science 

-Use descriptive statistics to summarize and explore data

-Calculate probability using basic rules

-Model data with probability distributions

-Describe the applications of different sampling methods 

-Calculate sampling distributions 

-Construct and interpret confidence intervals

-Conduct hypothesis tests

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The Nuts and Bolts of Machine Learning

 

What you'll learn

Identify characteristics of the different types of machine learning 

Prepare data for machine learning models 

Build and evaluate supervised and unsupervised learning models using Python

Demonstrate proper model and metric selection for a machine learning algorithm

Join Free: The Nuts and Bolts of Machine Learning

There are 5 modules in this course

This is the sixth of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn about machine learning, which uses algorithms and statistics to teach computer systems to discover patterns in data. Data professionals use machine learning to help analyze large amounts of data, solve complex problems, and make accurate predictions. You’ll focus on the two main types of machine learning: supervised and unsupervised. You'll learn how to apply different machine learning models to business problems and become familiar with specific models such as Naive Bayes, decision tree, random forest, and more.  

Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. 

Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.  

By the end of this course, you will:

-Apply feature engineering techniques using Python

-Construct a Naive Bayes model

-Describe how unsupervised learning differs from supervised learning

-Code a K-means algorithm in Python 

-Evaluate and optimize the results of K-means model

-Explore decision tree models, how they work, and their advantages over other types of supervised machine learning

-Characterize bagging in machine learning, specifically for random forest models 

-Distinguish boosting in machine learning, specifically for XGBoost models 

-Explain tuning model parameters and how they affect performance and evaluation metrics

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Regression Analysis: Simplify Complex Data Relationships

 

What you'll learn

Investigate relationships in datasets

Identify regression model assumptions 

Perform linear and logistic regression using Python

Practice model evaluation and interpretation

Join Free: Regression Analysis: Simplify Complex Data Relationships

There are 6 modules in this course

This is the fifth of seven courses in the Google Advanced Data Analytics Certificate. Data professionals use regression analysis to discover the relationships between different variables in a dataset and identify key factors that affect business performance. In this course, you’ll practice modeling variable relationships. You'll learn about different methods of data modeling and how to use them to approach business problems. You’ll also explore methods such as linear regression, analysis of variance (ANOVA), and logistic regression.  

Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. 

Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. 

By the end of this course, you will:

-Explore the use of predictive models to describe variable relationships, with an emphasis on correlation

-Determine how multiple regression builds upon simple linear regression at every step of the modeling process

-Run and interpret one-way and two-way ANOVA tests

-Construct different types of logistic regressions including binomial, multinomial, ordinal, and Poisson log-linear regression models

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Agile Project Management

 

What you'll learn

Explain the Agile project management approach and philosophy, including values and principles.

Discuss the pillars of Scrum and how they support Scrum values.

Describe the five important Scrum events and how to set up each event for a Scrum team.

Explain how to coach an Agile team and help them overcome challenges.

Join Free: Agile Project Management

There are 4 modules in this course

This is the fifth course in the Google Project Management Certificate program. This course will explore the history, approach, and philosophy of Agile project management, including the Scrum framework. You will learn how to differentiate and blend Agile and other project management approaches. As you progress through the course, you will learn more about Scrum, exploring its pillars and values and comparing essential Scrum team roles. You will discover how to build, manage, and refine a product backlog, implement Agile’s value-driven delivery strategies, and define a value roadmap. You will also learn strategies to effectively organize the five important Scrum events for a Scrum team, introduce an Agile or Scrum approach to an organization, and coach an Agile team. Finally, you will learn how to search for and land opportunities in Agile roles. Current Google project managers will continue to instruct and provide you with the hands-on approaches, tools, and resources to meet your goals.

Learners who complete this program should be equipped to apply for introductory-level jobs as project managers. No previous experience is necessary.

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

 - Explain the Agile project management approach and philosophy, including values and principles.

 - Explain the pillars of Scrum and how they support Scrum values.

 - Identify and compare the essential roles in a Scrum team and what makes them effective.

 - Build and manage a Product Backlog and perform Backlog Refinement.

 - Describe the five important Scrum events and how to set up each event for a Scrum team.

 - Implement Agile’s value-driven delivery strategies and define a value roadmap.

 - Explain how to coach an Agile team and help them overcome challenges.

 - Conduct a job search for an Agile role and learn how to succeed in your interview.

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Google Project Management: Professional Certificate

 

What you'll learn

Gain an immersive understanding of the practices and skills needed to succeed in an entry-level project management role

Learn how to create effective project documentation and artifacts throughout the various phases of a project

Learn the foundations of Agile project management, with a focus on implementing Scrum events, building Scrum artifacts, and understanding Scrum roles

Practice strategic communication, problem-solving, and stakeholder management through real-world scenarios

Join Free: 

Professional Certificate - 6 course series

Prepare for a new career in the high-growth field of project management, no experience required. Get professional training designed by Google and get on the fastrack to a competitively paid job.

Project managers are natural problem-solvers. They set the plan and guide teammates, and manage changes, risks, and stakeholders.

Over 6 courses, gain in-demand skills that will prepare you for an entry-level job. Learn from Google employees whose foundations in project management served as launchpads for their own careers. At under 10 hours per week, you can complete in less than six months.

This program qualifies you for over 100 hours of project management education, which helps prepare you for 

Project Management Institute

 Certifications like the globally-recognized 

Certified Associate in Project Management (CAPM)®

Join FREE : Google Project Management: Professional Certificate

Applied Learning Project

This program includes over 140 hours of instruction and hundreds of practice-based assessments which will help you simulate real-world project management scenarios that are critical for success in the workplace.

The content is highly interactive and exclusively developed by Google employees with decades of experience in program and project management.

Skills you’ll gain will include: Creating risk management plans; Understanding process improvement techniques; Managing escalations, team dynamics, and stakeholders; Creating budgets and navigating procurement; Utilizing  project management software, tools, and templates; Practicing Agile project management, with an emphasis on Scrum.

Through a mix of videos, assessments, and hands-on activities, you’ll get introduced to initiating, planning, and running both traditional and Agile projects. You’ll develop a toolbox to demonstrate your understanding of key project management elements, including managing a schedule, budget, and team.

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Technical Support Fundamentals

 

Build your Support and Operations expertise

This course is part of the Google IT Support Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts

Gain a foundational understanding of a subject or tool

Develop job-relevant skills with hands-on projects

Earn a shareable career certificate from Google

Join Free:Technical Support Fundamentals

There are 6 modules in this course

This course is the first of a series that aims to prepare you for a role as an entry-level IT Support Specialist. In this course, you’ll be introduced to the world of Information Technology, or IT. You’ll learn about the different facets of Information Technology, like computer hardware, the Internet, computer software, troubleshooting, and customer service. This course covers a wide variety of topics in IT that are designed to give you an overview of what’s to come in this certificate program.

By the end of this course, you’ll be able to:

● understand how the binary system works

● assemble a computer from scratch

● choose and install an operating system on a computer

● understand what the Internet is, how it works, and the impact it has in the modern world

● learn how applications are created and how they work under the hood of a computer

● utilize common problem-solving methodologies and soft skills in an Information Technology setting

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Google IT Support Professional Certificate

 

What you'll learn

Gain skills required to succeed in an entry-level IT job

Learn to perform day-to-day IT support tasks including computer assembly, wireless networking, installing programs, and customer service

Learn how to provide end-to-end customer support, ranging from identifying problems to troubleshooting and debugging

Learn to use systems including Linux, Domain Name Systems, Command-Line Interface, and Binary Code

Join Free:Google IT Support Professional Certificate

Prepare for a career in IT Support

Receive professional-level training from Google

Demonstrate your proficiency in portfolio-ready projects

Earn an employer-recognized certificate from Google

Qualify for in-demand job titles: IT Specialist, Tech Support Specialist, IT Support Specialist

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Process Data from Dirty to Clean

 

What you'll learn

Define data integrity with reference to types of integrity and risk to data integrity

Apply basic SQL functions for use in cleaning string variables in a database

Develop basic SQL queries for use on databases

Describe the process involved in verifying the results of cleaning data

There are 6 modules in this course

This is the fourth course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you’ll continue to build your understanding of data analytics and the concepts and tools that data analysts use in their work. You’ll learn how to check and clean your data using spreadsheets and SQL as well as how to verify and report your data cleaning results. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.

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

 - Learn how to check for data integrity.

 - Discover data cleaning techniques using spreadsheets. 

 - Develop basic SQL queries for use on databases.

 - Apply basic SQL functions for cleaning and transforming data.

 - Gain an understanding of how to verify the results of cleaning data.

 - Explore the elements and importance of data cleaning reports.

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Analyze Data to Answer Questions

 

What you'll learn

Discuss the importance of organizing your data before analysis with references to sorts and filters

Demonstrate an understanding of what is involved in the conversion and formatting of data

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

Describe the use of functions to conduct basic calculations on data in spreadsheets

There are 4 modules in this course

This is the fifth course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you’ll explore the “analyze” phase of the data analysis process. You’ll take what you’ve learned to this point and apply it to your analysis to make sense of the data you’ve collected. You’ll learn how to organize and format your data using spreadsheets and SQL to help you look at and think about your data in different ways. You’ll also find out how to perform complex calculations on your data to complete business objectives. You’ll learn how to use formulas, functions, and SQL queries as you conduct your analysis. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.

By the end of this course, you will:

 - Learn how to organize data for analysis.

 - Discover the processes for formatting and adjusting data. 

 - Gain an understanding of how to aggregate data in spreadsheets and by using SQL.

 - Use formulas and functions in spreadsheets for data calculations.

 - Learn how to complete calculations using SQL queries.

JOIN FREE - Analyze Data to Answer Questions

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Go Beyond the Numbers: Translate Data into Insights

 

What you'll learn

Apply the exploratory data analysis (EDA) process

Explore the benefits of structuring and cleaning data

Investigate raw data using Python

Create data visualizations using Tableau 

There are 5 modules in this course

This is the third of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn how to find the story within data and tell that story in a compelling way. You'll discover how data professionals use storytelling to better understand their data and communicate key insights to teammates and stakeholders. You'll also practice exploratory data analysis and learn how to create effective data visualizations. 

Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you build your data analytics skills to prepare for your career. 

Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.  

By the end of this course, you will:

-Use Python tools to examine raw data structure and format

-Select relevant Python libraries to clean raw data

-Demonstrate how to transform categorical data into numerical data with Python

-Utilize input validation skills to validate a dataset with Python

-Identify techniques for creating accessible data visualizations with Tableau

-Determine decisions about missing data and outliers 

-Structure and organize data by manipulating date strings

Join Free- Go Beyond the Numbers: Translate Data into Insights

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Decisions, Decisions: Dashboards and Reports

 

What you'll learn

Design BI visualizations

Practice using BI reporting and dashboard tools

Create presentations to share key BI insights with stakeholders

Develop professional materials for your job search

There are 6 modules in this course

You’re almost there! This is the third and final course in the Google Business Intelligence Certificate. In this course, you’ll apply your understanding of stakeholder needs, plan and create BI visuals, and design reporting tools, including dashboards. You’ll also explore how to answer business questions with flexible and interactive dashboards that can monitor data over long periods of time.

Google employees who currently work in BI will guide you through this course by providing hands-on activities that simulate job tasks, sharing examples from their day-to-day work, and helping you build business intelligence skills to prepare for a career in the field. 

Learners who complete the three courses in this certificate program will have the skills needed to apply for business intelligence jobs. This certificate program assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.  

By the end of this course, you will:

-Explain how BI visualizations answer business questions

-Identify complications that may arise during the creation of BI visualizations

-Produce charts that represent BI data monitored over time

-Use dashboard and reporting tools

-Build dashboards using best practices to meet stakeholder needs

-Iterate on a dashboard to meet changing project requirements

-Design BI presentations to share insights with stakeholders

-Create or update a resume and prepare for BI interviews

Join Free - Decisions, Decisions: Dashboards and Reports

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Ask Questions to Make Data-Driven Decisions

 

What you'll learn

Explain how each step of the problem-solving road map contributes to common analysis scenarios.

Discuss the use of data in the decision-making process.

Demonstrate the use of spreadsheets to complete basic tasks of the data analyst including entering and organizing data.

Describe the key ideas associated with structured thinking.

There are 4 modules in this course

This is the second course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. You’ll build on your understanding of the topics that were introduced in the first Google Data Analytics Certificate course. The material will help you learn how to ask effective questions to make data-driven decisions, while connecting with stakeholders’ needs. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.

By the end of this course, you will:

- Learn about effective questioning techniques that can help guide analysis. 

- Gain an understanding of data-driven decision-making and how data analysts present findings.

- Explore a variety of real-world business scenarios to support an understanding of questioning and decision-making.

- Discover how and why spreadsheets are an important tool for data analysts.

- Examine the key ideas associated with structured thinking and how they can help analysts better understand problems and develop solutions.

- Learn strategies for managing the expectations of stakeholders while establishing clear communication with a data analytics team to achieve business objectives.

Join Free- Ask Questions to Make Data-Driven Decisions

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Google Data Analytics Capstone: Complete a Case Study

 

What you'll learn

Differentiate between a capstone, case study, and a portfolio

Identify the key features and attributes of a completed case study

Apply the practices and procedures associated with the data analysis process to a given set of data

Discuss the use of case studies/portfolios when communicating with recruiters and potential employers

There are 4 modules in this course

This course is the eighth course in the Google Data Analytics Certificate. You’ll have the opportunity to complete an optional case study, which will help prepare you for the data analytics job hunt. Case studies are commonly used by employers to assess analytical skills. For your case study, you’ll choose an analytics-based scenario. You’ll then ask questions, prepare, process, analyze, visualize and act on the data from the scenario. You’ll also learn other useful job hunt skills through videos with common interview questions and responses, helpful materials to build a portfolio online, and more. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.

By the end of this course, you will:

 - Learn the benefits and uses of case studies and portfolios in the job search.

 - Explore real world job interview scenarios and common interview questions.

 - Discover how case studies can be a part of the job interview process. 

 - Examine and consider different case study scenarios. 

 - Have the chance to complete your own case study for your portfolio.

Join FREE - Google Data Analytics Capstone: Complete a Case Study

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Foundations: Data, Data, Everywhere

 

What you'll learn

Define and explain key concepts involved in data analytics including data, data analysis, and data ecosystem

Conduct an analytical thinking self assessment giving specific examples of the application of analytical thinking

Discuss the role of spreadsheets, query languages, and data visualization tools in data analytics

Describe the role of a data analyst with specific reference to jobs/positions

There are 5 modules in this course

This is the first course in the Google Data Analytics Certificate. These courses will equip you with the skills you need to apply to introductory-level data analyst jobs. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions. In this course, you’ll be introduced to the world of data analytics through hands-on curriculum developed by Google. The material shared covers plenty of key data analytics topics, and it’s designed to give you an overview of what’s to come in the Google Data Analytics Certificate. Current Google data analysts will instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.

By the end of this course, you will:

- Gain an understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job. 

- 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. 

- 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. 

- Evaluate the role of analytics in the data ecosystem. 

- Conduct an analytical thinking self-assessment. 

- Explore job opportunities available to you upon program completion, and learn about best practices in the job search.

Join Free - Foundations: Data, Data, Everywhere

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Google Business Intelligence Professional Certificate

 

What you'll learn

Explore the roles of business intelligence (BI) professionals within an organization

Practice data modeling and extract, transform, load (ETL) processes that meet organizational goals 

Design data visualizations that answer business questions

Create dashboards that effectively communicate data insights to stakeholders

Professional Certificate - 3 course series

Get professional training designed by Google and take the next step in your career with advanced skills in the high-growth field of business intelligence. There are over 166,000 open jobs in business intelligence and the median salary for entry-level roles is $96,000.¹

Business intelligence professionals collect, organize, interpret, and report on data to help organizations make informed business decisions. Some responsibilities include measuring performance, tracking revenue or spending, and monitoring progress.

This certificate builds on your data analytics skills and experience to take your career to the next level. It's designed for graduates of the 

Google Data Analytics Certificate

 or people with equivalent data analytics experience. Expand your knowledge with practical, hands-on projects, featuring BigQuery, SQL, and Tableau.

After three courses, you’ll be prepared for jobs like business intelligence analyst, business intelligence engineer, business intelligence developer, and more. At under 10 hours a week, the certificate program can be completed in less than two months. Upon completion, you can apply for jobs with Google and over 150 U.S. employers, including Deloitte, Target, and Verizon.

75% of certificate graduates report a positive career outcome (e.g., new job, promotion or raise) within six months of completion2

¹Lightcast™ US Job Postings (Last 12 Months: 1/1/2022 – 12/31/2022) 

2Based on program graduate survey responses, US 2022

Applied Learning Project

This program includes over 70 hours of instruction and 50+ practice-based assessments, which will help you simulate real-world business intelligence scenarios that are critical for success in the workplace. The content is highly interactive and exclusively developed by Google employees with decades of experience in business intelligence. Through a mix of videos, assessments, and hands-on labs, you’ll get introduced to BI tools and platforms and key technical skills required for an entry-level job.

Platforms and tools you will learn include: BigQuery, SQL, Tableau

In addition to expert training and hands-on projects, you'll complete a portfolio project that you can share with potential employers to showcase your new skill set. Learn concrete skills that top employers are hiring for right now.

Join free - Google Business Intelligence Professional Certificate

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Foundations of Data Science

 

What you'll learn

Understand common careers and industries that use advanced data analytics

Investigate the impact data analysis can have on decision-making

Explain how data professionals preserve data privacy and ethics 

Develop a project plan considering roles and responsibilities of team members

There are 5 modules in this course

This is the first of seven courses in the Google Advanced Data Analytics Certificate, which will help develop the skills needed to apply for more advanced data professional roles, such as an entry-level data scientist or advanced-level data analyst. Data professionals analyze data to help businesses make better decisions. To do this, they use powerful techniques like data storytelling, statistics, and machine learning. In this course, you’ll begin your learning journey by exploring the role of data professionals in the workplace. You’ll also learn about the project workflow PACE (Plan, Analyze, Construct, Execute) and how it can help you organize data projects.   

Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. 

Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.  

By the end of this course, you will:

-Describe the functions of data analytics and data science within an organization

-Identify tools used by data professionals 

-Explore the value of data-based roles in organizations 

-Investigate career opportunities for a data professional 

-Explain a data project workflow 

-Develop effective communication skills

Join free - Foundations of Data Science

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Google Cybersecurity Professional Certificate

 

What you'll learn

Understand the importance of cybersecurity practices and their impact for organizations.

Identify common risks, threats, and vulnerabilities, as well as techniques to mitigate them.

Protect networks, devices, people, and data from unauthorized access and cyberattacks using Security Information and Event Management (SIEM) tools.

Gain hands-on experience with Python, Linux, and SQL.

Prepare for a career in cybersecurity

Receive professional-level training from Google

Demonstrate your proficiency in portfolio-ready projects

Earn an employer-recognized certificate from Google

Qualify for in-demand job titles: cybersecurity analyst, security analyst, security operations center (SOC) analyst

Professional Certificate - 8 course series

Prepare for a new career in the high-growth field of cybersecurity, no degree or experience required. Get professional training designed and delivered by subject matter experts at Google and have the opportunity to connect with top employers.

Organizations must continuously protect themselves and the people they serve from cyber-related threats, like fraud and phishing. They rely on cybersecurity to maintain the confidentiality, integrity, and availability of their internal systems and information. Cybersecurity analysts use a collection of methods and technologies to safeguard against threats and unauthorized access — and to create and implement solutions should a threat get through.

During the 8 courses in this certificate program, you’ll learn from cybersecurity experts at Google and gain in-demand skills that prepare you for entry-level roles like cybersecurity analyst, security operations center (SOC) analyst, and more. At under 10 hours per week, you can complete the certificate in less than 6 months. 

Upon completion of the certificate, you can directly apply for jobs with Google and over 150 U.S. employers, including American Express, Deloitte, Colgate-Palmolive, Mandiant (now part of Google Cloud), T-Mobile, and Walmart.

The Google Cybersecurity Certificate helps prepare you for the CompTIA Security+ exam, the industry leading certification for cybersecurity roles. You’ll earn a dual credential when you complete both.

Applied Learning Project

This program includes 170 hours of instruction and hundreds of practice-based assessments and activities that simulate real-world cybersecurity scenarios that are critical for success in the workplace. Through a mix of videos, assessments, and hands-on labs, you’ll become familiar with the cybersecurity tools, platforms, and skills required for an entry-level job.

Skills you’ll gain will include: Python, Linux, SQL, Security Information and Event Management (SIEM) tools, Intrusion Detection Systems (IDS), communication, collaboration, analysis, problem solving and more! 

Additionally, each course includes portfolio activities through which you’ll showcase examples of cybersecurity skills that you can share with potential employers. Acquire concrete skills that top employers are hiring for right now.

Join Free - Google Cybersecurity Professional Certificate

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Automating Real-World Tasks with Python

 

What you'll learn

Use Python external libraries to create and modify documents, images, and messages

Understand and use Application Programming Interfaces (APIs) to interact with web services

Understand and use data serialization to send messages between running programs

Build a solution using the skills you have learned

There are 5 modules in this course

In the final course, we'll tie together the concepts that you’ve learned up until now. You'll tackle real-world scenarios in Qwiklabs that will challenge you to use multiple skills at once.

First, we'll take a closer look at how to use external Python modules to extend your code's capabilities, and spend some time learning how to use documentation to learn a new module. For example, we'll use the Python Image Library (PIL) to create and modify images. We'll show you some simple examples of how to perform common tasks in the course material, but it will be up to you to explore the module documentation to figure out how to solve specific problems.

Next, we'll show you how to communicate with the world outside of your code! You'll use data serialization to turn in-memory objects into messages that can be sent to other programs. Your program will send messages across the network to Application Programming Interfaces (APIs) offered by other programs. For those times when your code needs to talk to a person instead of a program, you'll also learn to send email messages.

At the end of this course, you’ll be able to take a description of a problem and use your skills to create a solution -- just like you would on the job. In your final capstone project, you'll be given a description of what your customer needs, and it will be up to you to create a program to do it!

JOIN - Automating Real-World Tasks with Python

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