## Introduction to Python

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

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148 results ## Introduction to Python

## Intermediate Python

## Introduction to Data Science in Python

## Data Manipulation with pandas

## Introduction to Statistics in Python

## Python Data Science Toolbox (Part 1)

## Supervised Learning with scikit-learn

## Introduction to Data Visualization with Matplotlib

## Joining Data with pandas

## Python Data Science Toolbox (Part 2)

## Introduction to Importing Data in Python

## Introduction to Data Visualization with Seaborn

## Exploratory Data Analysis in Python

## Cleaning Data in Python

## Writing Efficient Python Code

## Introduction to NumPy

## Introduction to Data Engineering

## Object-Oriented Programming in Python

## Writing Functions in Python

## Intermediate Importing Data in Python

## Unsupervised Learning in Python

## Sampling in Python

## Hypothesis Testing in Python

## Introduction to PySpark

## Machine Learning with Tree-Based Models in Python

## Introduction to Natural Language Processing in Python

## Introduction to Deep Learning in Python

## Introduction to Regression with statsmodels in Python

## Working with Dates and Times in Python

## Streamlined Data Ingestion with pandas

## Intermediate Data Visualization with Seaborn

## Machine Learning with scikit-learn

## Introduction to Python for Finance

## Web Scraping in Python

## Analyzing Police Activity with pandas

## Data Types for Data Science in Python

## Statistical Thinking in Python (Part 1)

## Building Dashboards with Dash and Plotly

## Manipulating Time Series Data in Python

## Unit Testing for Data Science in Python

## Introduction to Airflow in Python

## Regular Expressions in Python

## Big Data Fundamentals with PySpark

## Software Engineering for Data Scientists in Python

## Reshaping Data with pandas

## Introduction to Data Visualization with Plotly in Python

## Statistical Thinking in Python (Part 2)

## Introduction to TensorFlow in Python

## Introduction to Deep Learning with Keras

## Preprocessing for Machine Learning in Python

## Image Processing in Python

## Cluster Analysis in Python

## Linear Classifiers in Python

## Intermediate Python for Finance

## Cleaning Data with PySpark

## Extreme Gradient Boosting with XGBoost

## Machine Learning for Time Series Data in Python

## Time Series Analysis in Python

## Building Data Engineering Pipelines in Python

## Deep Learning with PyTorch

## Introduction to Databases in Python

## AI Fundamentals

## Dimensionality Reduction in Python

## Analyzing Marketing Campaigns with pandas

## Feature Engineering for NLP in Python

## ETL in Python

## Feature Engineering for Machine Learning in Python

## Introduction to Portfolio Risk Management in Python

## Developing Python Packages

## Dealing with Missing Data in Python

## Model Validation in Python

## Introduction to MongoDB in Python

## Introduction to Network Analysis in Python

## Writing Efficient Code with pandas

## Image Processing with Keras in Python

## Practicing Coding Interview Questions in Python

## Advanced Deep Learning with Keras

## ARIMA Models in Python

## Improving Your Data Visualizations in Python

## Intermediate Regression with statsmodels in Python

## Building Chatbots in Python

## Foundations of Probability in Python

## Working with Geospatial Data in Python

## Customer Analytics and A/B Testing in Python

## Credit Risk Modeling in Python

## Introduction to AWS Boto in Python

## Hyperparameter Tuning in Python

## Sentiment Analysis in Python

## Biomedical Image Analysis in Python

## Recurrent Neural Networks (RNN) for Language Modeling in Python

## Introduction to Spark SQL in Python

## Introduction to Linear Modeling in Python

## Importing and Managing Financial Data in Python

## Machine Learning with PySpark

## Visualizing Time Series Data in Python

## Winning a Kaggle Competition in Python

## Customer Segmentation in Python

## Advanced NLP with spaCy

## Monte Carlo Simulations in Python

## Supply Chain Analytics in Python

## Fraud Detection in Python

## Bayesian Data Analysis in Python

## Analyzing Social Media Data in Python

## Visualizing Geospatial Data in Python

## Quantitative Risk Management in Python

## Introduction to Predictive Analytics in Python

## Introduction to Portfolio Analysis in Python

## Marketing Analytics: Predicting Customer Churn in Python

## Statistical Simulation in Python

## Introduction to Financial Concepts in Python

## Building Recommendation Engines in Python

## Financial Trading in Python

## Machine Learning for Marketing in Python

## Python for Spreadsheet Users

## Machine Learning for Finance in Python

## Streaming Data with AWS Kinesis and Lambda

## Performing Experiments in Python

## Market Basket Analysis in Python

## Practicing Machine Learning Interview Questions in Python

## Python for R Users

## Designing Machine Learning Workflows in Python

## GARCH Models in Python

## Feature Engineering with PySpark

## Python for MATLAB Users

## Financial Forecasting in Python

## Case Study: School Budgeting with Machine Learning in Python

## Generalized Linear Models in Python

## Ensemble Methods in Python

## Case Studies in Statistical Thinking

## Building Recommendation Engines with PySpark

## Natural Language Generation in Python

## Spoken Language Processing in Python

## Practicing Statistics Interview Questions in Python

## Interactive Data Visualization with Bokeh

## Parallel Programming with Dask in Python

## Intermediate Network Analysis in Python

## Survival Analysis in Python

## Machine Translation in Python

## Command Line Automation in Python

## Analyzing IoT Data in Python

## Working with Categorical Data in Python

## HR Analytics: Predicting Employee Churn in Python

## Analyzing US Census Data in Python

## Bond Valuation and Analysis in Python

## Data Privacy and Anonymization in Python

## Predicting CTR with Machine Learning in Python

## Pandas Joins for Spreadsheet Users

## Intermediate Predictive Analytics in Python

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

4 hoursProgrammingHugo Bowne-Andersoncourses

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

4 hoursProgrammingHugo Bowne-Andersoncourses

Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.

4 hoursProgrammingHillary Green-Lermancourses

Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.

4 hoursData ManipulationRichie Cottoncourses

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

4 hoursProbability & StatisticsMaggie Matsuicourses

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

3 hoursProgrammingHugo Bowne-Andersoncourses

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

4 hoursMachine LearningGeorge Boormancourses

Learn how to create, customize, and share data visualizations using Matplotlib.

4 hoursData VisualizationAriel Rokemcourses

Learn to combine data from multiple tables by joining data together using pandas.

4 hoursData ManipulationAaren Stubberfieldcourses

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

4 hoursProgrammingHugo Bowne-Andersoncourses

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

3 hoursImporting & Cleaning DataHugo Bowne-Andersoncourses

Learn how to create informative and attractive visualizations in Python using the Seaborn library.

4 hoursData VisualizationDataCamp Content Creatorcourses

Learn how to explore, visualize, and extract insights from data.

4 hoursProbability & StatisticsAllen Downeycourses

Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

4 hoursImporting & Cleaning DataAdel Nehmecourses

Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.

4 hoursProgrammingLogan Thomascourses

Learn how to use NumPy arrays in Python to perform mathematical operations and wrangle data with the best of them!

4 hoursData ManipulationIzzy Webercourses

Learn about the world of data engineering with an overview of all its relevant topics and tools!

4 hoursData EngineeringVincent Vankrunkelsvencourses

Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.

4 hoursProgrammingAlex Yaroshcourses

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

4 hoursProgrammingShayne Mielcourses

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

2 hoursImporting & Cleaning DataHugo Bowne-Andersoncourses

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

4 hoursMachine LearningBenjamin Wilsoncourses

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

4 hoursProbability & StatisticsJames Chapmancourses

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

4 hoursProbability & StatisticsJames Chapmancourses

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

4 hoursProgrammingNick Solomoncourses

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

5 hoursMachine LearningElie Kawerkcourses

Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.

4 hoursMachine LearningKatharine Jarmulcourses

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

4 hoursMachine LearningDan Beckercourses

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in Python.

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

Learn how to work with dates and times in Python.

4 hoursProgrammingMax Shroncourses

Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.

4 hoursImporting & Cleaning DataAmany Mahfouzcourses

Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.

4 hoursData VisualizationChris Moffittcourses

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

4 hoursMachine LearningHugo Bowne-Andersoncourses

This course introduces Python for financial analysis.

4 hoursApplied FinanceAdina Howecourses

Learn to retrieve and parse information from the internet using the Python library scrapy.

4 hoursImporting & Cleaning DataThomas Laetschcourses

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

4 hoursData ManipulationKevin Markhamcourses

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

4 hoursProgrammingJason Myerscourses

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

3 hoursProbability & StatisticsJustin Boiscourses

Learn how to build interactive and insight-rich dashboards with Dash and Plotly.

4 hoursData VisualizationAlex Scrivencourses

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

4 hoursData ManipulationStefan Jansencourses

Learn how to write unit tests for your Data Science projects in Python using pytest.

4 hoursProgrammingDibya Chakravortycourses

Learn how to implement and schedule data engineering workflows.

4 hoursData EngineeringMike Metzgercourses

Learn about string manipulation and become a master at using regular expressions.

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

Learn the fundamentals of working with big data with PySpark.

4 hoursProgrammingUpendra Kumar Devisettycourses

Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.

4 hoursProgrammingAdam Spannbauercourses

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

4 hoursData ManipulationMaria Eugenia Inzaugaratcourses

Create interactive data visualizations in Python using Plotly.

4 hoursData VisualizationAlex Scrivencourses

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

4 hoursProbability & StatisticsJustin Boiscourses

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

4 hoursMachine LearningIsaiah Hullcourses

Learn to start developing deep learning models with Keras.

4 hoursMachine LearningMiguel Estebancourses

In this course you'll learn how to get your cleaned data ready for modeling.

4 hoursMachine LearningDataCamp Content Creatorcourses

Learn to process, transform, and manipulate images at your will.

4 hoursMachine LearningRebeca Gonzalezcourses

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

4 hoursMachine LearningShaumik Daityaricourses

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

4 hoursMachine LearningMike Gelbartcourses

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

4 hoursApplied FinanceKennedy Behrmancourses

Learn how to clean data with Apache Spark in Python.

4 hoursImporting & Cleaning DataMike Metzgercourses

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

4 hoursMachine LearningSergey Fogelsoncourses

This course focuses on feature engineering and machine learning for time series data.

4 hoursMachine LearningChris Holdgrafcourses

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

4 hoursProbability & StatisticsRob Reidercourses

Learn how to build data engineering pipelines in Python.

4 hoursData EngineeringKai Zhangcourses

Learn to create deep learning models with the PyTorch library.

4 hoursMachine LearningIsmail Elezicourses

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

4 hoursData ManipulationJason Myerscourses

Learn the fundamentals of AI. No programming experience required!

4 hoursMachine LearningNemanja Radojkovićcourses

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

4 hoursMachine LearningJeroen Boeyecourses

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

4 hoursCase StudiesJill Rosokcourses

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

4 hoursMachine LearningRounak Banikcourses

Leverage your Python and SQL knowledge to create a pipeline ingesting, transforming and loading data into a database.

4 hoursData EngineeringStefano Francavillacourses

Create new features to improve the performance of your Machine Learning models.

4 hoursMachine LearningRobert O'Callaghancourses

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

4 hoursApplied FinanceDakota Wixomcourses

Learn to create your own Python packages to make your code easier to use and share with others.

4 hoursProgrammingJames Fultoncourses

Learn how to identify, analyze, remove and impute missing data in Python.

4 hoursData ManipulationSuraj Donthicourses

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

4 hoursMachine LearningKasey Jonescourses

Learn to manipulate and analyze flexibly structured data with MongoDB.

4 hoursData ManipulationDonny Winstoncourses

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

4 hoursProbability & StatisticsEric Macourses

Learn efficient techniques in pandas to optimize your Python code.

4 hoursProgrammingLeonidas Souliotiscourses

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

4 hoursMachine LearningAriel Rokemcourses

Prepare for your next coding interviews in Python.

4 hoursProgrammingKirill Smirnovcourses

Build multiple-input and multiple-output deep learning models using Keras.

4 hoursMachine LearningZachary Deane-Mayercourses

Learn about ARIMA models in Python and become an expert in time series analysis.

4 hoursMachine LearningJames Fultoncourses

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.

4 hoursData VisualizationNicholas Strayercourses

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

4 hoursMachine LearningAlan Nicholcourses

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

5 hoursProbability & StatisticsAlexander A. Ramírez M.courses

This course will show you how to integrate spatial data into your Python Data Science workflow.

4 hoursData ManipulationJoris Van den Bosschecourses

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

4 hoursProbability & StatisticsRyan Grossmancourses

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

4 hoursApplied FinanceMichael Crabtreecourses

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

4 hoursProgrammingMaksim Pecherskiycourses

Learn to tune hyperparameters in Python.

4 hoursMachine LearningAlex Scrivencourses

Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

4 hoursMachine LearningVioleta Mishevacourses

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

4 hoursData ManipulationStephen Baileycourses

Use RNNs to classify text sentiment, generate sentences, and translate text between languages.

4 hoursMachine LearningDavid Cecchinicourses

Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.

4 hoursData ManipulationMark Plutowskicourses

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

4 hoursProbability & StatisticsJason Vestutocourses

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

5 hoursApplied FinanceStefan Jansencourses

Learn how to make predictions with Apache Spark.

4 hoursMachine LearningAndrew Colliercourses

Visualize seasonality, trends and other patterns in your time series data.

4 hoursData VisualizationThomas Vincentcourses

Learn how to approach and win competitions on Kaggle.

4 hoursMachine LearningYauhen Babakhincourses

Learn how to segment customers in Python.

4 hoursMachine LearningKarolis Urbonascourses

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

5 hoursMachine LearningInes Montanicourses

Learn to design and run your own Monte Carlo simulations using Python!

4 hoursProbability & StatisticsIzzy Webercourses

Leverage the power of Python and PuLP to optimize supply chains.

4 hoursMachine LearningAaren Stubberfieldcourses

Learn how to detect fraud using Python.

4 hoursMachine LearningCharlotte Wergercourses

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

4 hoursProbability & StatisticsMichał Oleszakcourses

In this course, you'll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

4 hoursData ManipulationAlex Hannacourses

Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

4 hoursData VisualizationMary van Valkenburgcourses

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

4 hoursApplied FinanceJamsheed Shorishcourses

In this course you'll learn to use and present logistic regression models for making predictions.

4 hoursMachine LearningNele Verbiestcourses

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

4 hoursApplied FinanceCharlotte Wergercourses

Learn how to use Python to analyze customer churn and build a model to predict it.

4 hoursCase StudiesMark Petersoncourses

Learn to solve increasingly complex problems using simulations to generate and analyze data.

4 hoursProbability & StatisticsTushar Shankercourses

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

4 hoursApplied FinanceDakota Wixomcourses

Learn to build recommendation engines in Python using machine learning techniques.

4 hoursMachine LearningRobert O'Callaghancourses

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

4 hoursApplied FinanceChelsea Yangcourses

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

4 hoursMachine LearningKarolis Urbonascourses

Use your knowledge of common spreadsheet functions and techniques to explore Python!

4 hoursProgrammingDataCamp Content Creatorcourses

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

4 hoursMachine LearningNathan Georgecourses

Learn how to work with streaming data using serverless technologies on AWS.

4 hoursData EngineeringMaksim Pecherskiycourses

Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

4 hoursProbability & StatisticsLuke Haydencourses

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

4 hoursMachine LearningIsaiah Hullcourses

Sharpen your knowledge in machine learning, and prepare for any potential question you might get in a machine learning interview in Python.

4 hoursMachine LearningLisa Stuartcourses

This course is for R users who want to get up to speed with Python!

5 hoursProgrammingDaniel Chencourses

Learn to build pipelines that stand the test of time.

4 hoursMachine LearningChristoforos Anagnostopouloscourses

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

4 hoursApplied FinanceChelsea Yangcourses

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

4 hoursData ManipulationJohn Hoguecourses

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

4 hoursProgrammingJustin Kigginscourses

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

4 hoursApplied FinanceVictoria Clarkcourses

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

4 hoursCase StudiesPeter Bullcourses

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

5 hoursProbability & StatisticsIta Cirovic Donevcourses

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

4 hoursMachine LearningRomán de las Herascourses

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

4 hoursProbability & StatisticsJustin Boiscourses

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

4 hoursMachine LearningJamen Longcourses

Imitate Shakespear, translate language and autocomplete sentences using Deep Learning in Python.

4 hoursMachine LearningBiswanath Haldercourses

Learn to load, transform, and transcribe human speech from raw audio files in Python.

4 hoursData ManipulationDaniel Bourkecourses

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

4 hoursProbability & StatisticsConor Deweycourses

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

4 hoursData VisualizationGeorge Boormancourses

Learn to upscale your Python workflows to efficiently handle big data with Dask.

4 hoursProgrammingJames Fultoncourses

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

4 hoursProbability & StatisticsEric Macourses

Use survival analysis to work with time-to-event data and predict survival time.

4 hoursProbability & StatisticsShae Wangcourses

Are you curious about the inner workings of the models that are behind products like Google Translate?

4 hoursMachine LearningThushan Ganegedaracourses

Learn to automate many common file system tasks and be able to manage and communicate with processes.

4 hoursProgrammingNoah Giftcourses

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

4 hoursData ManipulationMatthias Voppichlercourses

Learn how to manipulate and visualize categorical data using pandas and seaborn.

4 hoursData ManipulationKasey Jonescourses

In this course you'll learn how to apply machine learning in the HR domain.

4 hoursMachine LearningHrant Davtyancourses

Learn to use the Census API to work with demographic and socioeconomic data.

5 hoursCase StudiesLee Hachadooriancourses

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

4 hoursApplied FinanceJoshua Mayhewcourses

Learn to process sensitive information with privacy-preserving techniques.

4 hoursMachine LearningRebeca Gonzalezcourses

Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.

4 hoursMachine LearningKevin Huocourses

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

4 hoursData ManipulationJohn Millercourses

Learn how to prepare and organize your data for predictive analytics.

4 hoursMachine LearningNele Verbiestcourses