Data Analyst   

Welcome to the Data Analyst Career Academy. This comprehensive program is designed to equip aspiring analysts with the essential skills and knowledge needed to succeed in the rapidly evolving field of data analytics. Through this curriculum, you'll learn how to transform raw data into actionable insights, drive strategic decision-making, and improve business performance.

Throughout this program, you'll learn a wide array of data cleaning techniques, including data visualization, SQL querying, Excel analysis, and the fundamentals of data-driven decision-making. You’ll gain proficiency in popular BI platforms like Tableau, Power BI, and Google Analytics, as well as develop a deep understanding of data modeling, data analysis, and reporting.The Data Analyst Career Academy includes the Google Data Analytics Professional Certificate, the IBM Data analytics with Excel and R Professional Certificate, IBM Data Analyst Professional Certificate, the Meta Data Analyst Professional Certificate and the Google Cloud Data Analytics Professional Certificate. You will have 16 Guided Projects to help master new techniques and programs:

• Getting Started with Rstudio
• Joining Data in R using dplyr
• Interactive Statisitical Data Visualization 101
• Tidy Messy Data using tidyr in R
• Simulation of Covid-19 Testing Process Using R Simmer
• Forecast bikeshare demand using time sheries models in R
• Advanced Relational Database and SQL
• Exploratory vs Confirmatory data analysis using Python
• Analyze Data in a Model Care Database with MySQL Workbench
• Overview of Data Visualization
• Predictive Analytics for Business with H20 in R
• Transforming Data in R
• Build and Deploy a stroke prediction model using R
• Scrape and analyze data analyst job requirements with Python
• Excel for Beginners: Introduction to Spreadsheets
• Clean and analyze social media usage data with Python

The course combines video lectures, interactive labs, and real-world projects to ensure you not only learn but apply your knowledge effectively. With guided assessments and feedback, you will build a robust portfolio that showcases your skills to potential employers.

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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 over 251,000 open jobs in data analytics with a median entry-level salary of $95,000 in the U.S.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. At under 10 hours per week, you can complete the certificate in less than 6 months.

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Prepare for the in-demand field of data analytics. In this program, you’ll learn high valued skills like Excel, Cognos Analytics, and R programming language to get job-ready in less than 3 months.

Data analytics is a strategy-based science where data is analyzed to find trends, answer questions, shape business processes, and aid decision-making. This Professional Certificate focuses on data analysis using Microsoft Excel and R programming language. If you’re interested in using Python, please explore the IBM Data Analyst PC.

This program will teach you the foundational data skills employers are seeking for entry level data analytics roles and will provide a portfolio of projects and a Professional Certificate from IBM to showcase your expertise to potential employers.

You’ll learn the latest skills and tools used by professional data analysts and upon successful completion of this program, you will be able to work with Excel spreadsheets, Jupyter Notebooks, and R Studio to analyze data and create visualizations. You will also use the R programming language to complete the entire data analysis process, including data preparation, statistical analysis, data visualization, predictive modeling and creating interactive dashboards. Lastly, you’ll learn how to communicate your data findings and prepare a summary report.

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Prepare for a career in the high-growth field of data analytics. In this program, you’ll learn in-demand skills like Python, Excel, and SQL to get job-ready in as little as 4 months.

Data analysis is the process of collecting, storing, modeling, and analyzing data that can inform executive decision-making, and the demand for skilled data analysts has never been greater.

This program will teach you the foundational data skills employers are seeking for entry-level data analytics roles. It will not only help you start your career in data analytics, but also provides a strong foundation for future career development in other paths such as data science, artificial intelligence, deep learning, or data engineering.

You’ll learn the latest skills and tools used by professional data analysts including Excel spreadsheets, Python, Pandas, Numpy, Jupyter Notebooks, Cognos Analytics, and more. You’ll work with a variety of data sources and project scenarios to gain practical experience with data manipulation and applying analytical skills. You'll also have the option to learn how generative AI tools and techniques are used in data analysis.

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Prepare for a career in the high-growth field of data analytics. In this program, you’ll build in-demand technical skills like Python, Statistics, and SQL in spreadsheets to get job-ready in 5 months or less, no prior experience needed. You'll also have the option to learn how generative AI tools and techniques are used in data analytics.

Data analysis involves collecting, processing, and analyzing data to extract insights that can inform decision-making and strategy across an organization.

In this program, you’ll learn basic data analysis principles, how data informs decisions, and how to apply the OSEMN framework to approach common analytics questions. You’ll also learn how to use essential tools like SQL, Python, and Tableau to collect, connect, visualize, and analyze relevant data.

You’ll learn how to apply common statistical methods to writing hypotheses through project scenarios to gain practical experience with designing experiments and analyzing results.

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Become a data-driven powerhouse with Google Cloud! As a Cloud Data Analyst, you'll unlock insights hidden within vast datasets, transforming raw numbers into impactful stories that shape business strategies across the globe. This certificate program is your launchpad – a carefully curated mix of expert instruction and real-world challenges. You'll build a portfolio of impressive projects, showcasing to employers that you can analyze, visualize, and communicate data.

In this certificate program you’ll immerse yourself in the fundamentals of cloud data analytics. You’ll progressively build your working knowledge of how to structure, store, access, and visualize data using various Cloud tools and integration, such as Cloud Storage, BigQuery, Looker and Dataproc. The program will also touch on how AI is revolutionizing data analytics, from automating repetitive tasks to uncovering hidden insights.

No prior experience or degree is required to get started. This is where your journey begins – get ready to wield the tools and strategies that turn data into decisive action.

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In this 1-hour long project-based course, you will learn everything you need to know to get started with RStudio IDE, including how to install RStudio onto your Windows, MAC or Linux machine, how to use RStudio Cloud, a lightweight, cloud-based version of RStudio, how to start creating R projects, install and load R packages, as well as display interactive maps, graphs and tables with 1 line of code.

This course is perfect if you want to start learning R programming with RStudio: the Premiere IDE for R

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You will need to join or merge two or more data sets at different points in your work as a data enthusiast. The dplyr package offers very sophisticated functions to help you achieve the join operation you desire. This project-based course, "Joining Data in R using dplyr" is for R users willing to advance their knowledge and skills. In this course, you will learn practical ways for data manipulation in R. We will talk about different join operations and spend a great deal of our time here joining the sales and customers data sets using the dplyr package. By the end of this 2-hour-long project, you will perform inner join, full (outer) join, right join, left join, cross join, semi join, and anti join using the merge() and dplyr functions.

This project-based course is an intermediate-level course in R. Therefore, to get the most of this project, it is essential to have prior experience using R for basic analysis.

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In this guided project, we will explore plotly express to visualize statistical plots such as box plots, histograms, heatmaps, density maps, contour plots, and violin plots. Plotly express is a super powerful Python package that empowers anyone to create, manipulate and render graphical figures. This crash course is super practical and directly applicable to many industries such as banking, finance and tech industries.

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As data enthusiasts and professionals, our work often requires dealing with data in different forms. In particular, messy data can be a big challenge because the quality of your analysis largely depends on the quality of the data. This project-based course, "Tidy Messy Data using tidyr in R," is intended for beginner and intermediate R users with related experiences who are willing to advance their knowledge and skills.

In this course, you will learn practical ways for data cleaning, reshaping, and transformation using R. You will learn how to use different tidyr functions like pivot_longer(), pivot_wider(), separate_rows(), separate(), and others to achieve the tidy data principles. By the end of this 2-hour-long project, you will get hands-on massaging data to put in the proper format. By extension, you will learn to create plots using ggplot().

This project-based course is a beginner to an intermediate-level course in R. Therefore, to get the most out of this project, it is essential to have a basic understanding of using R.

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Welcome to "Simulation of Covid-19 Testing Process Using R Simmer". This is a project-based course which should take under 2 hours to finish. Before diving into the project, please take a look at the course objectives and structure.

By the end of this project, learn gain introductiory knowledge of Discrete Event Simulation, use R Studio and Simmer library, create statistical variables required for simulation, define process trajectory, define and assign resources, define arrivals (eg. incoming customers / work units), run simulation in R, store results in data frames, plot charts and interpret the results.

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In this project, you’ll help a bike rental company enhance its fleet management and pricing strategy by building a daily bike rental forecasting model using time series analysis techniques in R. Your objectives include loading, cleaning, processing, and analyzing daily rental transaction data, and developing and evaluating time series models for the most accurate predictions.

The company will use your validated forecasting model to determine the optimal number of bikes to keep in each station and set dynamic pricing based on predicted demand. Upon completion, you’ll be able to demonstrate your ability to perform a comprehensive data analysis project that involves answering critical business questions, extensive data visualization, and model selection.

There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers.

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In this 1-hour long project-based course, you will gain hands-on experience and learn about advanced SQL topics such as stored procedures, tiggers, functions, common table expressions and recursion. If you have intermediate level of experience with SQL and want to learn more, this course is for you!

Note: This is an advanced level course. Taking my course "Introduction to Relational Database and SQL" and "Intermediate Relational Database and SQL" before taking this course is highly recommended. Especially if you do not have any previous experience with relational database and SQL.

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This Guided Project, Exploratory and Confirmatory Data Analysis using python, is for those who want to learn about different methods of data analysis. In this 2-hour-long project-based course, you will understand and apply Exploratory Data Analysis, build different Data visualizations, apply different exploration techniques based on the data at hand and define and understand the concept of Confirmatory Data Analysis.

This project is unique because you will learn how and where to start your data exploration. You will also learn how to implement different data visualizations using python and when to use them. To be successful in this project, you will need to be experienced in python programming language and working with jupyter notebook environment.

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In this project, you’ll perform exploratory data analysis for Mint Classics Company, a retailer of model cars. The company is looking to close one of its storage facilities. Your objective is to recommend inventory reduction strategies that won’t negatively impact customer service.

Using MySQL Workbench, you’ll familiarize yourself with the sample database, run SQL queries to identify factors affecting storage space and propose inventory reduction approaches. Upon completion, you’ll demonstrate your ability to perform exploratory data analysis and present the results in a format that supports your recommendations.

There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers.

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This is a hands-on, guided project on Predictive Analytics for Business with H2O in R. By the end of this project, you will be able apply machine learning and predictive analytics to solve a business problem, explain and describe automatic machine learning, perform automatic machine learning (AutoML) with H2O in R. We will take a data-driven approach to predict the success of bank telemarketing.

H2O's AutoML automates the process of training and tuning a large selection of models, allowing the user to focus on other aspects of the data science and machine learning pipeline such as data pre-processing, feature engineering and model deployment.

To successfully complete the project, we recommend that you have prior experience with programming in R, basic machine learning theory, and have trained ML models in R. We will not be exploring how any particular model works nor dive into the math behind them. Instead, we assume you have this foundational knowledge and want to learn to use H2O in R for predictive analytics.

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In this 1-hour long project-based course, you will learn how to pivot data into wide and long format, split and combine cells and columns, handling missing values, select groups of observations and variables, and join data from different tables.

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In this project, you’ll help a leading healthcare organization build a model to predict the likelihood of a patient suffering a stroke. The model could help improve a patient’s outcomes. Working with a real-world dataset, you’ll use R to load, clean, process, and analyze the data and then train multiple classification models to determine the best one for making accurate predictions.

Upon completion, you’ll produce a well-validated prediction model that showcases your ability to perform a complete data analysis project involving feature engineering, handling missing data, model evaluation, model selection, and model deployment.

There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers.

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In this project, you’ll help a recruitment agency improve its job vacancy sourcing by using Python’s web-scraping capabilities to extract job postings from multiple sites.

This task will require you to write a Python script to extract job posting data from the source site and save it to a comma separated values (CSV) file. Your work will help the agency provide clients with with relevant job openings more quickly, giving them a competitive advantage over other applicants.

There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers.

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This 1-hour, project-based course is an introduction to spreadsheets. We’ll be using Excel on the Web in this project, which is the free spreadsheet program offered by Microsoft. However, all of the concepts that you will learn in this project will be applicable to other spreadsheet programs, such as LibreOffice Calc and Google Sheets.

We will cover the following concepts in a hands-on manner:

- Basic data entry, formatting and calculations
- Relative and absolute cell references
- Formulae and basic functions: sum, average, min, max
- Conditional formatting

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In this project, you'll serve as a data analyst at a marketing firm specializing in social media brand promotion. Your task is to use Python to extract, clean, and analyze tweets in specific categories (health, family, food, etc.) and generate visualizations.

Your analysis will provide valuable insights to help clients enhance their social media performance and allow the firm to deliver tweets on time and within budget, leading to faster results.

There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers.

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In this project, you will develop an understanding and appreciation for data visualization. You will review the benefits of data visualization as you examine existing examples of data that is displayed in a variety of visual formats. In addition, you will gain some hands-on experience in building your own data visualization examples by aggregating data and generating simple charts in Google Sheets.

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