APDS- Intro to Advanced Python for MLOps and Data Science

APDS: Intro to Advanced Python for MLOps and Data Science, available at Free, has an average rating of 4.1, with 15 lectures, 5 quizzes, based on 32 reviews, and has 2734 subscribers.

You will learn about Excel as a Data Scientist by unleashing your programming skills with Advanced Python Learn to write Higher Level programs by treating your code as data Create simpler, yet more sophisticated and maintainable, programs Scale yourself and your impact with reusable code This course is ideal for individuals who are Data Scientists who want to take their coding skills to the next level, learning advanced programming techniques in Python It is particularly useful for Data Scientists who want to take their coding skills to the next level, learning advanced programming techniques in Python.

Enroll now: APDS: Intro to Advanced Python for MLOps and Data Science

Summary

Title: APDS: Intro to Advanced Python for MLOps and Data Science

Price: Free

Average Rating: 4.1

Number of Lectures: 15

Number of Quizzes: 5

Number of Published Lectures: 15

Number of Published Quizzes: 5

Number of Curriculum Items: 20

Number of Published Curriculum Objects: 20

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Excel as a Data Scientist by unleashing your programming skills with Advanced Python

Learn to write Higher Level programs by treating your code as data

Create simpler, yet more sophisticated and maintainable, programs

Scale yourself and your impact with reusable code

Who Should Attend

Data Scientists who want to take their coding skills to the next level, learning advanced programming techniques in Python

Target Audiences

Data Scientists who want to take their coding skills to the next level, learning advanced programming techniques in Python

This is Advanced Python for Data Science!

Today, most people enter the world of Data Science through the buzz and allure of “AI.” We tackle Kaggle challenges, voraciously consume Stack Overflow, and eat, live, and breathe through the Jupyter Notebook. Python, along with its “killer app” of Machine Learning, has done nothing short of revolutionize the way we “do data science,” and the world is a more interesting place because of it!

Most of the time, your impact as a Data Scientist is limited by your ability to enact your ideas – not by the ideas themselves. You can train a model on ‘clean’ data using Scikit Learn or FastAI, or run an ANOVA, in a notebook. Enacting that idea means getting to the data in the first place. It means knowing how to store it. It means processing your data at scale. It means running your processing script, reliably, every day on fresh data. It means testing that script. It means collaborating on that script with a coworker – or 10 – as the project scales. It means curating a library and building tools to solve the same problem for 5 new projects. It means packaging a model up for distribution – sharing with another data scientist, or deploying it as a service.

It means changing the way you think about problems by adopting new paradigms that accelerate you – and your work – across your organization. It means building an approach to data science within the broader python ecosystem.

This is a course about how to be an Advanced Data Science Programmer, leveraging tools and techniques from the broader Python ecosystem. In this introductory course of the Advanced Python for MLOps and Data Science series, we will introduce you to the HEROS concept, and focus on Higher-Levels of coding.

You will learn how to treat your code as data, which is one of the most important ways to leverage Higher Levels of coding, and understand why repetitive code is a good opportunity to refactor into two parts – the purely “logical” part of your code, and the details – or “data”. We will then deep dive into real-world examples and see how we can produce many different outcomes, whether there are reports, analysis or models – with just few lines of logical code.

So, are you ready to take your next step in the MLOps and Advanced Python for Data Science Journey?

Buckle up, and let’s get coding!

Course Curriculum

Chapter 1: Introduction to Advanced Python for Data Science

Lecture 1: Sketch: Welcome!

Lecture 2: What is Advanced Python for Data Science

Lecture 3: What is This Course?

Lecture 4: Post it on IG: Summary of Today

Chapter 2: Code as Data

Lecture 1: Sketch: Why Code as Data

Lecture 2: Terminology: What is Code as Data

Lecture 3: Tech Intro: Assign Functions to Variable

Lecture 4: Functions of Functions

Lecture 5: Tech Intro: Exercise Assigning Functions to Variables

Lecture 6: Concepts: What Do We Gain Here?

Lecture 7: Daily Post

Chapter 3: Case Study

Lecture 1: Sketch: TikTok reports – Three Evaluations, One Class

Lecture 2: Tech Intro: Code-as-Data for TikTok Data Evaluation

Lecture 3: Tech Intro: Work Locally with The Starter Code

Lecture 4: Concepts: What do we gain here

Instructors

Scott Gorlin
Reproducible research through code

Pazpaz The Coder
Data Scientist

Albert Hurwitz
Data Scientist @ Liberty Mutual

Rating Distribution

1 stars: 2 votes

2 stars: 1 votes

3 stars: 6 votes

4 stars: 8 votes

5 stars: 15 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!