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Beyond Jupyter Notebooks

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Rating4.3
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Beyond Jupyter Notebooks, available at Free, has an average rating of 4.3, with 45 lectures, based on 161 reviews, and has 5904 subscribers.

You will learn about Docker Data Science Jupyter Python Data Analysis Data Visualization Open Source This course is ideal for individuals who are Any level of data scientists that want to accelerate their capabilities or Open Source Lover ❤️ or Pythonistas interested in Docker It is particularly useful for Any level of data scientists that want to accelerate their capabilities or Open Source Lover ❤️ or Pythonistas interested in Docker.

Enroll now: Beyond Jupyter Notebooks

Summary

Title: Beyond Jupyter Notebooks

Price: Free

Average Rating: 4.3

Number of Lectures: 45

Number of Published Lectures: 45

Number of Curriculum Items: 45

Number of Published Curriculum Objects: 45

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

  • Docker
  • Data Science
  • Jupyter
  • Python
  • Data Analysis
  • Data Visualization
  • Open Source

Who Should Attend

  • Any level of data scientists that want to accelerate their capabilities
  • Open Source Lover ❤️
  • Pythonistas interested in Docker

Target Audiences

  • Any level of data scientists that want to accelerate their capabilities
  • Open Source Lover ❤️
  • Pythonistas interested in Docker

Interactive notebooks like Jupyter have become more and more popular in the recent past and build the core of many data scientist’s workplace. Being accessed via web browser they allow scientists to easily structure their work by combining code and documentation. Yet notebooks often lead to isolated and disposable analysis artefacts. Keeping the computation inside those notebooks does not allow for convenient concurrent model training, model exposure or scheduled model retraining.

Those issues can be addressed by taking advantage of recent developments in the discipline of software engineering. Over the past years containerization became the technology of choice for crafting and deploying applications. Building a data science platform that allows for easy access (via notebooks), flexibility and reproducibility (via containerization) combines the best of both worlds and addresses Data Scientist’s hidden needs.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Watch Me First 🙂

Chapter 2: Analyze your Data (Jupyter/Docker)

Lecture 1: Introduction

Lecture 2: How to install Docker?

Lecture 3: Starting Jupyter

Lecture 4: Mapping Ports

Lecture 5: Running in detached Mode

Lecture 6: Facing a Persistence Problem

Lecture 7: Solving the Persistence Problem

Lecture 8: Course Project – Task

Lecture 9: Course Project – Solution

Chapter 3: Visualize your Data (Superset)

Lecture 1: Introduction

Lecture 2: Starting Superset

Lecture 3: Prepare Data

Lecture 4: Charts and Dashboards

Lecture 5: Course Project – Task

Lecture 6: Course Project – Solution

Chapter 4: Store your structured Data (Postgres)

Lecture 1: Introduction

Lecture 2: Starting Postgres

Lecture 3: Facing an Access Problem

Lecture 4: Docker-Compose (I/II)

Lecture 5: Docker-Compose (II/II)

Lecture 6: Solving the Access Problem

Lecture 7: Create a Custom User

Lecture 8: Course Project – Task

Lecture 9: Course Project – Solution

Chapter 5: Store your unstructured Data (Minio)

Lecture 1: Introduction

Lecture 2: Starting Minio

Lecture 3: GUI Interaction

Lecture 4: Programmatic Interaction

Lecture 5: Course Project – Task

Lecture 6: Course Project – Solution

Chapter 6: Expose your Model (API-Star)

Lecture 1: Introduction

Lecture 2: Starting API-Star

Lecture 3: API-Star and Docker

Lecture 4: Docker Enhancements

Lecture 5: Course Project – Task

Lecture 6: Course Project – Solution

Chapter 7: Automate your Analysis (Airflow)

Lecture 1: Introduction

Lecture 2: Basic Concepts

Lecture 3: Starting Airflow

Lecture 4: DAG Creation

Lecture 5: Course Project – Task

Lecture 6: Course Project – Solution

Chapter 8: Wrap Up

Lecture 1: Wrap Up

Lecture 2: BONUS: Cookiecutter Template

Instructors

Rating Distribution

  • 1 stars: 3 votes
  • 2 stars: 3 votes
  • 3 stars: 22 votes
  • 4 stars: 58 votes
  • 5 stars: 75 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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