Beyond Jupyter Notebooks
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
-
Joshua Görner
Product Engineer | Ex-Data Scientist | Father
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
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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