In today’s digital age, data is more than just numbers; it’s a treasure trove of insights waiting to be unearthed. The Google Data Analytics Professional Certificate Course which is by far one of the Best Online Certification for Data science, equips you an aspiring data Analyst with the skills to navigate and harness the potential of data. No matter the experience level, Whether you’re a novice looking to step into the world of data or an experienced professional aiming to upskill, this program provides a transformative learning journey that will shape your career progression .This is your path to a career in data analytics As it is one of the Best Online Certification for Data science. In this program, you’ll learn in-demand skills that will have you job-ready in less than 6 months. No degree or experience is required.
What you’ll learn
Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job
Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau)
Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming
Learn how to visualize and present data findings in dashboards, presentations, and commonly used visualization platforms.
Prepare for a new career in the high-growth field of data analytics, no experience or degree required. Get professional training designed by Google and have the opportunity to connect with top employers. There are 483,000 open jobs in data analytics with a median entry-level salary of $92,000.¹
Data analytics is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making.
Over 8 courses, gain in-demand skills that prepare you for an entry-level job. You’ll learn from Google employees whose foundations in data analytics served as launchpads for their own careers making it somewhat the Best Online Certification for Data science. At under 10 hours per week, you can complete the certificate in less than 6 months.
Upon completion, you can directly apply for jobs with Google and over 150 U.S. employers, including Deloitte, Target, Verizon, and Google.
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 (2022: Jan. 1, 2022 – Dec. 31, 2022)
²Based on the program graduate survey, United States 2022
Applied Learning Project
This program includes over 180 hours of instruction and hundreds of practice-based assessments, which will help you simulate real-world data analytics 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 data analytics. Through a mix of videos, assessments, and hands-on labs, you’ll get introduced to analysis tools and platforms and key analytical skills required for an entry-level job.
Skills you’ll gain will include: Data cleaning, problem-solving, critical thinking, data ethics, and data visualization
Platforms and tools you will learn include: Presentations, Spreadsheets, SQL, Tableau, and R Programming
In addition to expert training and hands-on projects, you’ll complete a case study that you can share with potential employers to showcase your new skill set. Learn concrete skills that top employers are hiring for right now.
Professional Certificate
This certification program consists of an 8-course series that will give in-depth knowledge about Data Analytics.
1)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
2)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.
3)Prepare Data for Exploration
What you’ll learn
Explain factors to consider when making decisions about data collection
Discuss the difference between biased and unbiased data
Describe databases with references to their functions and components
Describe best practices for organizing data
4) 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
5) 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
6) Share Data Through the Art of Visualization
What you’ll learn
Describe the use of data visualizations to talk about data and the results of data analysis
Identify Tableau as a data visualization tool and understand its uses
Explain what data-driven stories are including reference to their importance and their attributes
Explain principles and practices associated with effective presentations
7) Data Analysis with R Programming
What you’ll learn
Describe the R programming language and its programming environment
Explain the fundamental concepts associated with programming in R including functions, variables, data types, pipes, and vectors
Describe the options for generating visualizations in R
Demonstrate an understanding of the basic formatting R Markdown to create structure and emphasize content
8) 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
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