Kamil Budny

Introduction to Python

Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with numpy.

Introduction to SQL

Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.

Introduction to R

Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

Intermediate Python

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

Python Data Science Toolbox (Part 1)

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

Supervised Learning with scikit-learn

Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

Data Engineering for Everyone

Discover how data engineers lay the groundwork that makes data science possible.

Joining Data in SQL

Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.

Intermediate R

Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

Python Data Science Toolbox (Part 2)

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

Merging DataFrames with pandas

This course is all about the act of combining, or merging, DataFrames, an essential part your Data Scientist's toolbox.

Introduction to Importing Data in Python

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

Introduction to the Tidyverse

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collect...

Statistical Thinking in Python (Part 1)

Build the foundation you need to think statistically and to speak the language of your data.

Intermediate Python for Finance

Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

pandas Foundations

Learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.

Introduction to Data Visualization in Python

Learn complex data visualization techniques using Matplotlib and seaborn.

Introduction to Deep Learning in Python

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.

Intermediate Importing Data in Python

Improve your Python data importing skills and learn to work with web and API data.

Data Manipulation in R with dplyr

Master techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.

Introduction to Data in R

Learn the language of data, study types, sampling strategies, and experimental design.

Unsupervised Learning in Python

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

Statistical Thinking in Python (Part 2)

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Introduction to Importing Data in R

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

Machine Learning with Tree-Based Models in Python

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using sciki...

Data Science for Business

Learn about data science and how can you use it to strengthen your organization.

Writing Functions in R

Learn the fundamentals of writing functions in R so you can make your code more readable and automate repetitive tasks.

Introduction to Databases in Python

In this course, you'll learn the basics of relational databases and how to interact with them.

Correlation and Regression in R

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

Introduction to Python for Finance

This course introduces Python for financial analysis.

Cluster Analysis in Python

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means c...

Reporting with R Markdown

Learn to create interactive analyses and automated reports with R Markdown.

Exploratory Data Analysis in R

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Cleaning Data in R

Learn to explore your data so you can properly clean and prepare it for analysis.

Data Visualization with ggplot2 (Part 1)

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

Manipulating DataFrames with pandas

You will learn how to tidy, rearrange, and restructure your data using versatile pandas DataFrames.

Case Study: School Budgeting with Machine Learning i...

Learn how to build a model to automatically classify items in a school budget.

Cleaning Data in Python

This course will equip you with all the skills you need to clean your data in Python.

Supervised Learning in R: Classification

In this course you will learn the basics of machine learning for classification.

Linear Classifiers in Python

In this course you will learn the details of linear classifiers like logistic regression and SVM.

Joining Data in R with dplyr

This course will show you how to combine data sets with dplyr's two table verbs.

Extreme Gradient Boosting with XGBoost

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve...

Intermediate Importing Data in R

Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

Manipulating Time Series Data in Python

In this course you'll learn the basics of working with time series data.

Case Study: Exploratory Data Analysis in R

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Introduction to R for Finance

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Time Series Analysis in R

Learn the core techniques necessary to extract meaningful insights from time series data.

Working with Dates and Times in R

Learn the essentials of parsing, manipulating and computing with dates and times in R.

Dimensionality Reduction in Python

Learn to reduce dimensionality in Python.

Interactive Data Visualization with Bokeh

Learn how to create versatile and interactive data visualizations using Bokeh.

Intermediate R: Practice

Strengthen your knowledge of the topics you learned in Intermediate R with a ton of new and fun exercises.

Introduction to Network Analysis in Python

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

Unsupervised Learning in R

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Cluster Analysis in R

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract in...

Manipulating Time Series Data with xts and zoo in R

The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

Forecasting in R

Learn how to make predictions about the future using time series forecasting in R.

Importing and Managing Financial Data in Python

In this course, you'll learn how to import and manage financial data in Python using various tools and sources.

Data Visualization with ggplot2 (Part 2)

Take your data visualization skills to the next level with coordinates, facets, themes, and best practices in ggplot2.

Intermediate R for Finance

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

ARIMA Models in R

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Credit Risk Modeling in R

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Introduction to Financial Concepts in Python

Using Python and NumPy, learn the most fundamental financial concepts.

Introduction to Portfolio Analysis in R

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

String Manipulation with stringr in R

Learn how to pull character strings apart, put them back together and use the stringr package.

Financial Trading in R

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

Importing and Managing Financial Data in R

Learn how to access financial data from local files as well as from internet sources.

Quantitative Risk Management in R

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Visualizing Time Series Data in R

Learn how to visualize time series in R, then practice with a stock-picking case study.

Intermediate Portfolio Analysis in R

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Importing & Cleaning Data in R: Case Studies

In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

Case Studies: Manipulating Time Series Data in R

Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.

Object-Oriented Programming with S3 and R6 in R

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

Sentiment Analysis in R: The Tidy Way

In this course, you will the learn principles of sentiment analysis from a tidy data perspective.

Bond Valuation and Analysis in R

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.