Data Science & Analytics   

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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Welcome to the Data Manager Career Academy. This comprehensive program is designed to equip aspiring data managers with the essential skills and knowledge needed to succeed in the dynamic and growing field of data management. Through this hands-on curriculum, you’ll learn how to oversee data operations, ensure data quality, and develop data governance strategies that support data-driven decision-making across organizations.

Throughout this program, you’ll gain expertise in key data management concepts such as data integration, data warehousing, and data security. You’ll learn how to effectively manage large datasets, implement data management frameworks, and use industry-standard tools like SQL, cloud platforms, and data modeling software. You’ll also explore best practices for data governance, privacy, and compliance, while developing skills in leading teams and managing data infrastructure.The Data Manager Career Academy includes the IBM Data Management Professional Certificate and 6 Guided Projects to help master new techniques and programs:

• Database Creation and Modeling using MySQL Workbench
• Aggregate Data in SQL using MySQL Workbench
• Introduction to Data Analysis using Microsoft Excel
• Data Visualization in Tableau: Create Dashboards and Stories
• Data Management with Databricks: Big Data with Delta Lakes
• Data Cleaning in Snowflake: Techniques to Clean Messy Data

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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Data management is projected to grow 140% by 2030 (IoT Analytics) and is a critical factor for an organization’s competitive edge. Now, more than ever, businesses need skilled data professionals to handle their data effectively.

This IBM Data Manager Professional Certificate equips you with the vital skills and hands-on experience employers seek to competently handle data collection, organization, and protection with accuracy, security, and accessibility while enabling teams to analyze it for decision-making, compliance, and operations.

You’ll gain job-ready skills through hands-on experience using industry-standard tools, including Excel spreadsheets, business intelligence (BI) tools like Tableau, and dashboard design tools such as IBM Cognos. You’ll work with databases including MySQL, PostgreSQL, and MongoDB. Plus, you’ll compare data architectures such as data warehouses, data marts, and data lakes.

You’ll explore core data concepts like relational database management systems (RDBMS) design, integration processes, migration strategies, security protocols, storage, SQL queries, administration, ETL and data pipelines, analysis, and cloud environments.

If you want to launch your data management career quickly, this IBM Professional Certificate gives you the sought-after skills and experience you need to talk about in interviews.

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Welcome to the Data Scientist Career Academy. This comprehensive program is designed to equip aspiring data scientists with the essential skills and knowledge needed to succeed in the rapidly evolving field of data science. Through this hands-on curriculum, you’ll learn how to transform raw data into actionable insights, build predictive models, and make data-driven decisions that drive business impact.

Throughout this program, you’ll gain proficiency in essential data science tools and technologies, including Python, R, SQL, and machine learning algorithms. You’ll dive into data wrangling, statistical analysis, data visualization, and data-driven storytelling. You’ll also explore key concepts in data modeling, model evaluation, and deploying machine learning models at scale. The Data Scientist Career Academy includes the IBM Data Science Professional Certificate, the Fractal Data Science Professional Certificate as well as have 7 Guided Projects to help master new techniques and programs:

• Transforming Data in R
• Exploratory vs Confirmatory data analysis using Python
• Simple Linear Regression for the Absolute Beginner
• Mining Quality Prediction Using Machine and Deep Learning
• Master Data Analysis with Pandas
• Getting Started with Rstudio
• Importing Data into R

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 career in the high-growth field of data science. In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist in as little as 4 months. No prior knowledge of computer science or programming languages is required.

Data science involves gathering, cleaning, organizing, and analyzing data with the goal of extracting helpful insights and predicting expected outcomes. The demand for skilled data scientists who can use data to tell compelling stories to inform business decisions has never been greater.

You’ll learn in-demand skills used by professional data scientists including databases, data visualization, statistical analysis, predictive modeling, machine learning algorithms, and data mining. You’ll also work with the latest languages, tools,and libraries including Python, SQL, Jupyter notebooks, Github, Rstudio, Pandas, Numpy, ScikitLearn, Matplotlib, and more.

Upon completing the full program, you will have built a portfolio of data science projects to provide you with the confidence to excel in your interviews. 

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Prepare for a new career in this high-demand field with a Professional Certificate from Fractal Analytics. Whether you're a recent graduate seeking a rewarding career shift or a professional aiming to upskill, this program will equip you with the essential skills demanded by the industry.

This curriculum is designed with a problem-solving approach at the center to equip and enable you with the skills, required to solve data science problems, instead of just focusing on the tools and applications.

Through hands-on courses you'll master Python programming, harness the power of machine learning, cultivate expertise in data manipulation, and build understanding of cognitive factors affecting decisions. You will also learn the direct application of tools like SQL, PowerBI, and Python to real-world scenarios.

Upon completion, you will earn a Professional Certificate, which will help to make your profile standout in your career journey.

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Welcome to the Data Warehouse Developer Career Academy, your comprehensive gateway to learning data warehouse engineering and launching a successful career in this dynamic field. This course is designed for aspiring data engineers, and data analysts looking to upskill, and anyone interested in understanding the intricacies of SQL, Relational Database Management Systems (RDBMS) and basic Shell scripting.

Throughout this program, you will gain hands-on experience with the fundamental concepts and technologies that drive modern networking. From foundational knowledge to advanced techniques, the Data Warehouse Developer Career Academy includes the IBM Data Warehouse Engineer Professional Certificate and 6 Guided Projects:

• Shell Scripting with Bash: Basics
• Advanced Relational Database and SQL
• Create a Database with the Modeling Toolin MySQL Workbench
• Linux: Introduction to Shell Scripting for DevOps
• Creating Azure Serverless Functions in a Real-World Scenario
• Using MySQL Database with PHP

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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This Professional Certificate is intended to help you develop the job-ready skills and portfolio for an entry-level Business Intelligence (BI) or Data Warehousing Engineering position. Throughout the online courses in this program, you will immerse yourself in the in-demand role of a Data Warehouse Engineer and acquire the essential skills you need to work with a range of tools and databases to design, deploy, operationalize and manage Enterprise Data Warehouses (EDW).

By the end of this Professional Certificate, you will be able to perform the key tasks required in a data warehouse engineering role. You will work with Relational Database Management Systems (RDBMS) and query data using SQL statements.

You will use Linux/UNIX shell scripts to automate repetitive tasks, and build data pipelines with tools like Apache Airflow and Kafka to Extract, Transform and Load (ETL) data. You will gain experience with managing databases and data warehouses.

Finally, you will design and populate data warehouse systems and utilize Business Intelligence tools to analyze and extract insights using reports and dashboards.

This program is suitable for anyone with a passion for learning and is suitable for you whether you have a college degree or not and does not require any prior data engineering, or programming experience.

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In this project, you will learn how to use Bash for creating basic shell scripts. After completing the 1-hour hands-on guided project, you'll know how to automatically rename a collection of files, read the contents of a file line by line and use all basic constructs of Bash.

Note: It's recommended that you have some experience with the command line before starting this project. Consider looking into the project 'Practical introduction to the Command Line' first - https://www.coursera.org/projects/practical-introduction-to-the-command-line.

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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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In this project you will use the Modeling and Design Tool in MySQL Workbench to design and create a multiple-table relational database. As a DBMS (database management system), MySQL is used by many organizations for managing a variety of types and sizes of databases. MySQL Workbench acts as an integrated development environment allowing users to work with relational databases using a visual user interface rather than the command line. Hands-on activities include using the Modeling and Design Tool to draw a database design diagram, generating the database from that diagram, and then using MySQL Workbench features to load data into the database tables. You will also find an optional Challenge Task and an optional Capstone task for extra practice.

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In this 1-hour long project-based course on Linux: Introduction to Shell Scripting for DevOps, you will be writing your own Bash/Shell scripts for scratch.You will be going through all of the key components that make up the bash script, from exit statuses, the test command, if/else statements, loops and file archiving. You will no longer be completely confused when looking at Bash scripts, and will have a working knowledge which allows you to start working with scripts yourself.

This course is designed for any person working or who intends to work with Linux, from Linux system administrators to developers and DevOps practitioners. Or even if you are a student who is curious to get comfortable with Linux this course is for you also.

This is an intermediate level course and is designed for an individual who has a beginner's knowledge of the Linux/Unix command line and Unix crud practices in computer science.

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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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Serverless computing and Microservices development have become a robust technology and methodology to decoupling monolithic and legacy systems, creating new services, and increasing digital transformation and innovation. In this project, you will learn how to develop some Serverless Microservices using Microsoft Azure Functions that are part of the Microsoft Cloud Platform in a Real-World Scenario example. Once you’re done with this project, you will be able to develop Azure Functions using Visual Studio Code and deploy them to Azure Cloud and create some HTML pages to be the front-end that will call and use the microservices functions, just with a few steps.

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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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Hello everyone and welcome to this hands-on guided project on simple linear regression for the absolute beginner. In simple linear regression, we predict the value of one variable Y based on another variable X. X is called the independent variable and Y is called the dependent variable. This guided project is practical and directly applicable to many industries. You can add this project to your portfolio of projects which is essential for your next job interview.

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In this 1-hour long project-based course, you will be able to identify and fully comprehend the basics of the MYSQL workbench and create a new connection to the local server. you will also learn how to create a new database and drop it, create new tables, and delete them. Moreover, You will be able to rename columns of a table, connect tables with each other, and add data to tables. And finally, you will learn how to add columns and apply some features professionally on these columns using some keywords such as PRIMARY KEY, FOREIGN KEY, NOT NULL, AUTO_INCREMENT, and DISTINCT and update the tables with new data. SQL is used by all the big names in tech like Netflix or Airbnb. If you target Google, Facebook, or Amazon, they, of course, have their database systems. But SQL will be there too to query and analyze the data.

This guided project is for beginners in the field of data management data modeling and databases. It provides you with the basics of creating the whole database. It equips you with knowledge of the first steps in modeling.

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In this project you will use MySQL Workbench to write SQL queries that aggregate (group) data. Incorporating aggregate functions like COUNT, SUM, and AVG, your SQL queries will group and summarize data. Data that is aggregated and presented in a logical format makes it a more valuable decision-making tool for users.

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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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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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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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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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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 1-hour long project-based course, you will learn how to read all sorts of data and import them into R, including CSV files, Excel files, data from other statistical software, the web and from relational databases.

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Use Tableau Web Authoring to create best practice dashboards and stories from data

In this Guided Project, you will:

Develop a best practice interactive dashboard for data exploration, including using dashboard actions for interactivity

Develop a best practice interactive dashboard for reporting, including using filters for interactivity

Develop a best practice data story to put across an argument, justified by data

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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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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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In this 1.5-hour long project-based course, you will be able to:
- Understand the theory and intuition behind Simple and Multiple Linear Regression.
- Import Key python libraries, datasets and perform data visualization
- Perform exploratory data analysis and standardize the training and testing data.
- Train and Evaluate different regression models using Sci-kit Learn library.
- Build and train an Artificial Neural Network to perform regression.
- Understand the difference between various regression models KPIs such as MSE, RMSE, MAE, R2, and adjusted R2.
- Assess the performance of regression models and visualize the performance of the best model using various KPIs.

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In this structured series of hands-on guided projects, we will master the fundamentals of data analysis and manipulation with Pandas and Python. Pandas is a super powerful, fast, flexible and easy to use open-source data analysis and manipulation tool. 

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In this 2-hour guided project, "Data Management with Databricks: Big Data with Delta Lakes" you will collaborate with the instructor to achieve the following objectives:

1-Create Delta Tables in Databricks and write data to them. Gain hands-on experience in setting up and managing Delta Tables, a powerful data storage format optimized for performance and reliability.

2-Transform a Delta table using Python and leverage SQL to query the data for creating a comprehensive dashboard. Learn how to apply Python-based transformations to Delta Tables, and use SQL queries to extract the necessary insights for building a Supply Chain dashboard.

3-Utilize Delta Lake's merge operation and version control capabilities to efficiently update Delta Tables. Explore the capabilities of Delta Lake's merge operation to perform upserts and other data updates efficiently. Additionally, learn how to leverage Delta Lake's built-in version control to track and access previous versions of Delta Tables as needed.

Throughout a real-world business scenario, you will use Databricks to build an end-to-end data pipeline that integrates various JSON data files and applies transformations, ultimately providing valuable insights and analysis-ready data.

This intermediate-level guided project is designed for data engineers who build data pipelines for their companies using Databricks. In order to be successful in this guided project, you need prior knowledge of writing Python scripts including importing libraries, setting-up variables, manipulating data frames, and using functions. You will also need to be familiar with writing SQL queries such as aggregating, filtering, and joining tables.

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This 2.5 hours-long guided project is designed for business analysts & data engineers eager to learn how to Clean Messy Data in Snowflake Data Platform.

By the end of the project, you will:
-Be able to identify common data quality issues then use SQL String functions to remove unwanted characters and split rows into multiple columns.
-Extract dates from Text fields then use SQL date functions for comparisons and calculations.
-Identify and correct missing and duplicated data then answer business questions using SQL statements.

To achieve these objectives, we will work on a real example from the field, you will play the role of a Data Analyst in the marketing department, who has been tasked with answering a business question, but the customer data they have received presents several data quality challenges.

Note: To be successful in this project you need to have Snowflake beginner knowledge such as Creating a trial account, Databases, Tables, and Virtual Warehouses.

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In this 1.5 hour project, you will combine your knowledge of HTML, object-oriented PHP, SQL, and MySQL to make a dynamic website that uses MySQL database on the web server. You will learn two different methods, one applies to 12 other SQL databases and one specific to MySQL. Basic HTML, object-oriented PHP, relational database, and SQL required as prerequisites. Completing my courses "Build an Automobile Listing Website with PHP" and "Learn Object-Oriented Programming with PHP" first is highly recommended.

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