### SQL Fundamentals

**Learn how to extract data from databases using SQL.**

- How to use SQL to explore and extract data
- How to use SQL to organize data
- How to write SQL queries to find summary statistics
- How to query across multiple tables
- How to answer business questions using SQL

### Machine Learning Introduction with Python

**Learn how machine learning can help you make predictions with data.**

- The basics of machine learning, including avoiding common pitfalls and evaluating model performance
- Common techniques like k-nearest neighbours, k-means clustering, and decision trees
- Foundational mathematics for machine learning, including calculus and linear algebra

### Machine Learning Intermediate with Python

**Learn more advanced machine learning techniques with Python.**

- How to work with neural networks
- The basics of building a machine learning project from start to finish
- How to build a machine learning model and make your first Kaggle submission
- How to select the best algorithm and tune your model for best performance

### Data Visualization with R

**Learn how to use R for data visualization.**

- How to visualize changes overtime with line graphs
- How to use histograms to understand data distributions
- How to compare groups using bar charts and box plots
- How to understand relationships between variables using scatter plots

### Data Analysis and Visualization with Python

**Learn how Python and Pandas simplify data analysis and visualization.**

- How to use Python libraries Pandas and NumPy for data analysis
- How to use the most common data visualization techniques to explore data
- How to use data visualization to convey insights and tell a story
- Techniques for manipulating and cleaning data

### APIs and Web Scraping with R

**Learn how to acquire data from APIs and the web with R.**

- How to query external data sources with an API using R
- The basics of scraping data from the web

### Python Basics for Data Analysis

**Introduce yourself to the python programming language.**

- Fundamentals of programming in Python
- How to use Jupyter notebooks
- How to work with text, date, and time data
- Basics of object-oriented programming in Python

### Probability and Statistics with Python

**Learn probability and statistics for more robust data analysis.**

- Basics of statistical analysis, including sampling, working with variables, and understanding frequency distribution tables
- How to summarize a distribution's measures of central tendency and variability
- The fundamentals of probability and how to use them for analysis
- How to create and test hypotheses using significance testing

### R Basics for Data Analysis

**Introduce yourself to the R programming language.**

- The fundamentals of programming in R
- How to use control and flow iteration
- How to work with and create your own functions
- The basics of working with strings and dates

### APIs and Web Scraping with Python

**Learn how to acquire data from APIs and the web with Python.**

- How to query external data sources with an API using Python
- The basics of scraping data from the web

### Probability and Statistics with R

**Learn probability and statistics for more robust data analysis.**

- The basics of statistical analysis, including sampling, working with variables, and understanding frequency distribution tables
- How to summarize a distribution's measures of central tendency and variability
- The fundamentals of probability and how to use them for analysis
- How to create and test hypotheses using significance testing

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