Live Tutorials and Project Walkthroughs
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Upcoming Live Events
Intro to machine learning and deep learning for complete beginners
In our next live webinar on December 8 at 6:30 PM UTC, you can join Dataquest founder and CEO Vik Paruchuri for "Intro to Machine Learning and Deep Learning for Complete Beginners." No prior machine learning or deep learning experience is necessary.Register NowPast Tutorials
Watch recordings of our previous live sessions.
Deploy a Deep Learning API to the Cloud with Docker and Azure
In this video, we'll deploy a deep learning translation API to the cloud. First, we'll build a dockerfile and an image. Then, we'll deploy the image to Azure Container Registry and run the image using Azure Container Instances.
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Create a Deep Learning API with Python and FastAPI
In this video, we'll build a translation API using deep learning. Using FastAPI, we'll create a web server that exposes a /translate route and a /results route. By the end, we'll have a web server that can run translation jobs quickly.
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Weather Prediction with Python and Machine Learning (with Code)
In this video, we'll predict tomorrow's temperature using Python and historical data. We'll build a system to make historical predictions, and we'll add more predictors to improve the model.
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How to Ace a Data Scientist Interview
In this video, our experts will give an overview of the current realities of the job market, and they will walk you through a typical data scientist interview process.
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Predict NBA Games Using Python and Machine Learning (Part 2)
In this video, we'll predict the winners of basketball games in the NBA using Python. We'll start by reading in box score data that we scraped in part 1 of this series.
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Web Scraping NBA Games Using Python (Part 1)
In this video, we'll learn how to scrape NBA box scores using Python and combine them into a pandas DataFrame that you can use for machine learning or data analysis.
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Detect Dog Emotions with Deep Learning (Full Walkthrough with Code)
In this video, we'll determine which emotion a dog is feeling based on a picture. Using deep learning and PyTorch, we'll analyze images and predict three emotions: happy, sad, or relaxed.
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Create Your First Data Solution in the Cloud
In this video, we'll walk you through an end-to-end scenario visualizing COVID-19 case data loaded into Azure Cosmos DB from Azure Blob Storage using Azure Data Factory. Then, we'll visualize that data using the Integrated Power BI Experience enabled by the Azure Synapse Link for Azure Cosmos DB.
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Predict Baseball Stats Using Machine Learning and Python
In this video, we'll predict future season stats for baseball players using machine learning. The stat we'll focus on is the wins above replacement (WAR) a player will generate next season.
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Predict Bitcoin Prices Using Machine Learning and Python (with Full Code)
In this video, we'll predict the future price of Bitcoin using historical price and sentiment data. We'll use data on the USD/BTC price from Yahoo Finance, along with data from Wikipedia about edits to the Bitcoin page.
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Predict House Prices Using Machine Learning and Python (Full Tutorial)
In this video, we'll predict future house prices by training a machine learning model to predict whether prices will rise or fall. We'll write all of our code in Python using JupyterLab, and we'll use data from the U.S. Federal Reserve, along with house price data from Zillow.
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3 Real-World Data Projects for Your Portfolio
In this video, we will go in-depth with three data science case studies to see how companies leverage data science to make better decisions, innovate in their sectors, and meet customers’ specific needs.
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Build a Custom Search Engine in Python with Filtering
In this video, we'll build a custom search engine that uses filtering to rank results. The engine will get results from the Google Custom Search API, store them, then rank them based on filters we define. We'll filter based on the number of trackers on the page and the length of the content. The framework will be extensible, so you can add your own filters, including ones that use machine learning.
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Ridge Regression from Scratch in Python (Machine Learning Tutorial)
In this video, we'll fully implement the ridge regression algorithm from scratch in python. We'll define ridge regression, including the theory and equation. Then we'll implement it in Python and compare it to the reference implementation from scikit-learn. We'll conclude by learning how to calculate the optimal penalty lambda.
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Linear Regression Algorithm in Python from Scratch (Beginner Tutorial)
Linear regression is the most popular machine learning algorithm, and the easiest way to understand how it works is simply to implement it. In this video, we'll show you how to build a linear regression model from scratch, including learning the theory and the math.
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Build Your First Machine Learning Project (Full Beginner Walkthrough)
Machine learning can be intimidating for beginners, but in this tutorial, we'll walk you through a real-world project, step by step. By the end, you'll understand machine learning, you'll know why machine learning is useful, and you'll be able to train your own machine learning model.
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7 Beginner Python Data Projects (with Full Code and Walkthroughs)
Here are seven beginner data projects in Python, with full code and walkthroughs. Get started with these to build an awesome project portfolio and impress your future employers.
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K-means Clustering Algorithm in Python From Scratch (Beginner Tutorial)
Here's a step-by-step project tutorial video that will show you how to build a k-means clustering algorithm using Python — and real data from FIFA.
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Understanding Different Data Roles (a Roundtable Discussion)
In this roundtable discussion, Dataquest graduates and data professionals offer an inside look into different data roles. They share insights from their past and current data roles, discuss what they do today, identify the skills they rely on, and cover how they interact with other data professionals.
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Business Analyst Job Outlook in 2022 (a Panel Discussion)
In this panel discussion, Dataquest founder and CEO Vik Paruchuri and Dataquest graduates and business analysts Aaron Melton and Viktoria Jorayeva discuss 2022 data career trends and the emerging demand for business analysts.
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Real-Time Speech Recognition Using Your Microphone (Beginner Tutorial with Full Code)
In this tutorial, we'll use Python and Jupyter to build a real-time speech recognition system that uses your microphone. By the end, you'll have a functional Jupyter notebook that can record microphone audio, transcribe it, and display it.
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Speech Recognition and Summarization System in Python (Project Tutorial)
In this tutorial, we'll build a system that can recognize speech in audio files, generate a transcript, and then summarize it. By the end, you'll have a full speech recognition system that will run locally on your computer to transcribe and summarize podcasts, lecture notes, meeting recordings, and more.
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Build an Airflow Data Pipeline to Download Podcasts (Beginner Data Engineer Tutorial)
In this beginner tutorial, we'll build a data pipeline that can download and store podcast episodes using Apache Airflow, a powerful and widely used data engineering tool.
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How to Build a Data Project Portfolio and Stand Out to Employers (with Examples)
In this video, we'll cover how to create a high-quality project portfolio that will help you stand out to employers. We'll go over why you need a portfolio, some project examples, a method for creating projects, how to present your portfolio, and where to get ideas for projects.
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Learner Roundtable Discussion: How to Start a Career in Data Science
In this discussion, Dataquest graduates share their experiences, stories, tips, and advice on how to prepare for and stay relevant in the data science industry.
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Build a Movie Recommendation System with Jupyter and Pandas
In this project walkthrough, we'll learn how to create a movie recommendation system using Jupyter, Python, and Pandas. By the end, we'll be able to type the name of a movie into an input box and instantly get recommendations for other movies we might like.
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Predict the Stock Market with Machine Learning
In this tutorial, we'll learn how to predict tomorrow's S&P 500 index price using historical data. We'll start by downloading and cleaning the data with pandas to prepare for machine learning. Then, we'll train a random forest model and make predictions using backtesting.
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How to Start Your Career in Data
In this video, we'll cover how to find the right data role, how to learn the skills you need to get hired, and how to showcase your skills to employers.
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Is Power BI Certification Worth It?
In this video, Dataquest Founder and CEO Vik Paruchuri and Microsoft Content Developer David Moring discuss the value of a Power BI certification — and how it can help you shape your career.
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Predicting Football Match Winners with Machine Learning
In this video, we'll use machine learning to predict who will win football matches in the EPL. We'll start by cleaning the EPL match data, then we'll create predictors and train a machine learning model to predict the winner of each football match.
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Web Scraping Football Matches from The EPL with Python (part 1 of 2)
In this video, we'll learn how to scrape football match data from the English Premier League. We'll download all of the matches for several seasons using Python and the requests library. We'll then parse and clean the data using BeautifulSoup and pandas.
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How to Become a Business Analyst (with Q&A)
In this video, we share some of the latest trends in business analytics, how to get into the field, and how to stay relevant in an ever-changing technological landscape.
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Classifying Dog Images with Deep Learning and TensorFlow
In this video, we'll walk through an end-to-end deep learning project using TensorFlow and Keras. We'll read in a dataset of dog images, then we'll train a convolutional neural network to classify them by breed.
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Power BI Beginner Tutorial: Analyzing the Olympics
In this beginner tutorial, we'll walk through the main features of Microsoft Power BI — the Power Query Editor, DAX, the M language, and the Report View. We'll do this by analyzing data on the Olympics from 1896 to 2016.
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Web Scraping Beginner Tutorial with Playwright
In this video, we'll extract, parse, and work with data from websites using Python, Playwright, and BeatifulSoup.
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Exploring FIFA Stats with Microsoft Power BI
In this video, we'll look at some of the main features of Power BI, including visualizations, reports, data exploration, the Power Query Editor, and the M language.
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Analyzing COVID RNA Sequences with Python
In this project walkthrough, we'll analyze the RNA sequences of COVID, including the delta and omicron variants.
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Analyzing Data with Microsoft Power BI
In this video, we'll give you an overview of our new skill path, "Analyzing Data with Microsoft Power BI," and we'll talk about the increasing demand for business analysis — and why you should learn Microsoft Power BI.
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Using Collaborative Filtering to Recommend Books (part 2 of 2)
In this video, we'll build on part 1 of this series and customize our book recommendations with collaborative filtering.
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Building a Book Recommendation System with Python (part 1 of 2)
In this video, we'll learn how to build a system to recommend new books.
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Predicting the Weather with Machine Learning (Beginner Project)
In this video, we'll learn how to predict your local weather with machine learning.
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Predicting the NBA MVP: Machine Learning Project (part 3 of 3)
This is part 3 of a series wherein we predict which NBA player will win MVP! You can watch this without having seen parts 1 or 2.
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Cleaning NBA Stats Data with Python And Pandas: Data Project (part 2 of 3)
This is part 2 of a series wherein we predict which NBA player will win MVP. You can watch this without having seen part 1.
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Web Scraping NBA Stats with Python: Data Project (Part 1 of 3)
In this video, we'll download NBA stats using web scraping.
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Analyzing Star Wars Survey Data with Python and Pandas (Data Project)
In this video, we'll walk through a beginner data cleaning project using Python and pandas. We'll analyze Star Wars survey data and create graphs.
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Predicting Stock Prices with Python and Scikit-Learn (Machine Learning Project)
In this video, we'll walk through a data science project to predict stock market prices using Python, scikit-learn, and pandas.
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