Python Programming Course

In this course, we will have a full overview of Python programming. We will start with fundamental Python functionality such as arithmetic, conditional statements, and working with basic data structures. We will then expand upon our working knowledge of data structures to work with full-blown datasets in the Pandas package. Within Pandas, we will be able to extract CSVs and Excel files of data, manipulate columns and rows, filter data, group together categories, and much more. Finally, once we’re able to tweak and transform datasets for analysis, we will discuss making basic visualizations in Python, which will allow us to take our insights and analysis to the next level.

Course Curriculum

Intro to Statistics for Data Science Course

To succeed in Data Science, statistical knowledge is a must have skill, so it is a must-have skill for data scientists. Having a command of programming and tools is only one aspect, without a deep understanding of statistics, we will not be able to ask the right questions or effectively interpret data. In this concise course you will quickly get up to speed on the most fundamental statistical concepts needed for Data Science.

1. Intro to Data Science Statistics

2. Telling a Story with Data

3. Charts and Tables - Part 1

4. Charts and Tables - Part 2

5. Summarising the Data

6. Introduction to Probability - Part 1

7. Introduction to Probability - Part 2

8. Introduction to Probability - Part 3

9. Expectations & Variance

10. Covariance & Correlation

11. Discrete Variables

12. Continuous Variables

Course Curriculum

Excel: Beginner To Intermediate Course

This concise course is perfect for getting complete beginners comfortable with Excel as well as those who have been away from Excel for a long time. In fact, I recommend all students at the very least work through this once to ensure you are prepared for the more advanced material to come. By the end of this approximate 90mins of training, you will be at an Intermediate level of understanding Excel.

1. Navigating around Excel

2. Entering Information

3. Navigating without the Mouse

4. Basic Formatting

5. Dragging & Autofill

6. Copy & Paste

7. Clearing cells

8. Inserting & Deleting

9. Date Basics

10. Introduction to Formulas

11. Introduction to Formulas: Part 2

12. Introduction to Formulas: Autosum

13. More on Worksheets

14. More Borders

15. Printing considerations

16. Conditional Formatting

17. Charts

18. Autofilter

19. Sorting Data

20. Introduction to Text Data

21. Named Ranges

22. Data Validation

23. Advanced Data Formatting

Course Curriculum

Machine Learning Course

This course is jam-packed with everything you need to get started with machine learning. We will look at various algorithm types, such as linear regression, logistic regression, decision trees, random forest, ensembled models, and beyond. Each model type will have lectures devoted to conceptualizing its mechanics, with some easy-to-follow math as well. In addition to conceptual lectures, there will be accompanying videos on key data science theory to improve accuracy and avoid common model pitfalls. Finally, each model type will have a coding video in Python to demonstrate the algorithm in action. We will also discuss common tips and tricks for cleaning data in preparation for machine learning, as well as an overview of machine learning in R.

R Programming Course

To be a well-rounded data scientist, it is imperative to know the ins and outs of both Python and R, the latter of which we will discuss in this course. In addition to all the primary coding functionality, we will learn more about what makes R unique, diving into how R leverages vectors and matrices to read in and work with data.

Additionally, we will discuss the mechanics of the powerful dplyr library, which allows extreme ease in manipulating datasets. We will then discuss data visualization, highlighting the advantages of the highly customizable ggplot2 library, which powers some of the most intricate graphs seen in data journalism and research today.

Finally, we will go through basic statistics and discuss the statistical tools within R, such as constructing confidence intervals, hypothesis testing, and ANOVA testing.

Python for Web Development - Build the game Snake Online Course

In this course we will be building the classic game Snake with Python! We have found that even for experienced professionals, learning in a fun and engaging way like this will keep you motivated as you navigate through the challenge of learning a new coding language.

MODULE 1

Drawing to the screen

MODULE 2

Movement based on keyboard input

MODULE 3  

Increase snake length when eating and adjusting speed

Course Curriculum

Data Science Careers Course

This course contains everything you need to know about Data Science Business Applications. In the Career Overview section you will become familiar with the many and varied Data Science roles and understand the overlaps between them.

 I will also be running through some of my own projects that were created with a business mindset to grab the attention of employers and colleagues. Additionally, we will talk through some of the common questions that occur in data science interviews that pertain to coding, statistics, and general data science acumen. 

Then we will walk through some additional exercises to prepare for data science coding challenges, as well as discuss resumes and cover letters as they pertain to the world of data science. Section 3 takes you through examples of real projects and how to go about finding data Finally, we end with an overview of additional data analysis software such as Github, SQL Tableau and Excel