Pallav BAKSHI

Introduction to Python

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

Introduction to R

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

Introduction to SQL

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

Intermediate Python

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

Introduction to Data Visualization in Python

Learn complex data visualization techniques using Matplotlib and seaborn.

Supervised Learning with scikit-learn

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

Intermediate R

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

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.

pandas Foundations

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

Python Data Science Toolbox (Part 2)

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

Introduction to Deep Learning in Python

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

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.

Statistical Thinking in Python (Part 1)

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

Merging DataFrames with pandas

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

Data Visualization with ggplot2 (Part 1)

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

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.

Introduction to Data in R

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

Cleaning Data in R

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

Cleaning Data in Python

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

Intermediate Importing Data in Python

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

Unsupervised Learning in Python

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

Introduction to PySpark

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Manipulating DataFrames with pandas

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

Correlation and Regression in R

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

Exploratory Data Analysis in R

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

Statistical Thinking in Python (Part 2)

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

Data Manipulation in R with dplyr

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

Intermediate Importing Data in R

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

Introduction to Databases in Python

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

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 Network Analysis in Python

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

Data Visualization with ggplot2 (Part 2)

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

Multiple and Logistic Regression in R

In this course you'll learn to add multiple variables to linear models and to use logistic regression for classificat...

Introduction to Machine Learning

Learn to train and assess models performing common machine learning tasks such as classification and clustering.

Interactive Data Visualization with Bokeh

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

Reporting with R Markdown

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

Data Visualization in R

This course provides a comprehensive introduction to working with base graphics in R.

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 Study: School Budgeting with Machine Learning i...

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

Case Study: Exploratory Data Analysis in R

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

Joining Data in R with dplyr

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

Image Processing with Keras in Python

Learn powerful techniques for image analysis in Python using deep learning and convolutional neural networks in Keras.

Unsupervised Learning in R

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

Machine Learning with caret in R

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Intermediate R: Practice

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

Foundations of Inference in R

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Data Analysis in R, the data.table Way

Master core concepts in data manipulation such as subsetting, updating, indexing and joining your data using data.table.

Data Types for Data Science in Python

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them t...

Machine Learning with Tree-Based Models in R

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

Data Visualization with ggplot2 (Part 3)

This course covers some advanced topics including strategies for handling large data sets and specialty plots.

Text Mining with Bag-of-Words in R

Learn the bag of words technique for text mining with R.

Financial Trading in R

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

Building Recommendation Engines with PySpark

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Spatial Statistics in R

Learn how to make sense of spatial data and deal with various classes of statistical problems associated with it.