Data science has become an essential tool in industries ranging from tech to agriculture. This class will teach the core concept of data science to deliver a high-level understanding of the expectations, steps, and vocabulary to work with and manage data scientists. The goal is to enable data-driven decisions, as well as, introduce the data-curious to data science.
This class will not include programming or software but teach general concepts that are tool-agnostic and can be applied in multiple contexts. This will include the high-level understanding necessary in projects to manage data science teams eventually. If you’d prefer an applied class and already know Python I recommend this class on Skillshare.
This class is for people wanting to understand the principles behind data science without a coding background. Whether these will be applied in Excel, Tableau, or Python, the principles are general purpose and help build a better data-driven analysis.
Moreover, this course comes with a worksheet for risk assessment of your data science projects.
Sign up for Skillshare No-Code Data Science Masterclass and get a free trial.
Business analytics and data science have become important skills across all industries. Knowing both how to perform analytics, as well as, sense checking analyses and understanding concepts is key in making decisions today.
Python has become the lingua franca of data science and is, therefore, the topic of this class. This class assumes Python knowledge if you’d prefer a high-level introduction without programming application to data science I have another class: The No-Code Data Science Master Class.
Programming can be intimidating, however, Python excels due to its readability and being freely available for all platforms including Linux, Mac and Windows. This class will assume some prior knowledge of Python syntax, but to establish a common learning environment some of the basics will be covered. We will cover the full data science workflow including:
Loading data from files (e.g. Excel tables) and databases (e.g. SQL servers)
Exploratory data analysis
Model validation and churn analysis
Data visualization and report generation
In this class, we will use freely and openly available Python libraries including: Jupyter, NumPy, SciPy, Pandas, MatPlotLib, Seaborn, and Scikit-Learn and you will also learn how to quickly learn new libraries.
Sign up for Skillshare Data Science with Python and get a free trial.