Data Analytics

Today we continue our Data Analyst Portfolio Project Series. In this project we will be taking some of the SQL queries we worked on in the first project and creating visualizations in Tableau. ____________________________________________ SUBSCRIBE! Do you want to become a Data Analyst? That's what this channel is all about! My goal is to help you learn everything you need in order to start your career or even switch your career into Data Analytics. Be sure to subscribe to not miss out on any content! ____________________________________________

Today we continue our Data Analyst Portfolio Project Series. In this project we will be cleaning data in SQL. Data Cleaning is a super underrated skill in the Data Analyst community so I hope this can be helpful to start you on your journey to learning that skill. ____________________________________________ SUBSCRIBE! Do you want to become a Data Analyst? That's what this channel is all about! My goal is to help you learn everything you need in order to start your career or even switch your career into Data Analytics. Be sure to subscribe to not miss out on any content!

Today we continue our Data Analyst Portfolio Project Series. In this project we will be working in Python to find correlations between variables. ____________________________________________ SUBSCRIBE! Do you want to become a Data Analyst? That's what this channel is all about! My goal is to help you learn everything you need in order to start your career or even switch your career into Data Analytics. Be sure to subscribe to not miss out on any content! ____________________________________________

Today we start our Data Analyst Portfolio Project Series. In our first project we will be using SQL to do some Data Exploration. We will then visualize the data in Tableau for our next project. Link to GitHub: https://bit.ly/3xNwzGK Link to Dataset: https://ourworldindata.org/covid-deaths ** It appears the dataset may have been changed at the source. Please use these 2 links to get the data from the 2 excels: 1. Covid Deaths: https://github.com/AlexTheAnalyst/Por... 2. Covid Vaccinations: https://github.com/AlexTheAnalyst/Por...

Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the "sexiest job of the 21st century." You'll learn the important elements of data science. You'll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You'll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics. ⭐️ Course Contents ⭐️ ⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science - Welcome (1.1) - Demand for Data Science (2.1) - The Data Science Venn Diagram (2.2) - The Data Science Pathway (2.3) - Roles in Data Science (2.4) - Teams in Data Science (2.5) - Big Data (3.1) - Coding (3.2) - Statistics (3.3) - Business Intelligence (3.4) - Do No Harm (4.1) - Methods Overview (5.1) - Sourcing Overview (5.2) - Coding Overview (5.3) - Math Overview (5.4) - Statistics Overview (5.5) - Machine Learning Overview (5.6) - Interpretability (6.1) - Actionable Insights (6.2) - Presentation Graphics (6.3) - Reproducible Research (6.4) - Next Steps (7.1) ⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46) - Welcome (1.1) - Metrics (2.1) - Accuracy (2.2) - Social Context of Measurement (2.3) - Existing Data (3.1) - APIs (3.2) - Scraping (3.3) - New Data (4.1) - Interviews (4.2) - Surveys (4.3) - Card Sorting (4.4) - Lab Experiments (4.5) - A/B Testing (4.6) - Next Steps (5.1) ⌨️ Part 3: Coding (2:32:42) - Welcome (1.1) - Spreadsheets (2.1) - Tableau Public (2.2) - SPSS (2.3) - JASP (2.4) - Other Software (2.5) - HTML (3.1) - XML (3.2) - JSON (3.3) - R (4.1) - Python (4.2) - SQL (4.3) - C, C++, & Java (4.4) - Bash (4.5) - Regex (5.1) - Next Steps (6.1) ⌨️ Part 4: Mathematics (4:01:09) - Welcome (1.1) - Elementary Algebra (2.1) - Linear Algebra (2.2) - Systems of Linear Equations (2.3) - Calculus (2.4) - Calculus & Optimization (2.5) - Big O (3.1) - Probability (3.2) ⌨️ Part 5: Statistics (4:44:03) - Welcome (1.1) - Exploration Overview (2.1) - Exploratory Graphics (2.2) - Exploratory Statistics (2.3) - Descriptive Statistics (2.4) - Inferential Statistics (3.1) - Hypothesis Testing (3.2) - Estimation (3.3) - Estimators (4.1) - Measures of Fit (4.2) - Feature Selection (4.3) - Problems in Modeling (4.4) - Model Validation (4.5) - DIY (4.6) - Next Step (5.1)