Applied Python for Data Science and Analytics

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Jeff James

6:15:32

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1. Introduction and Getting Moving with Python

1. Introduction - whats this course about Should you take it.mp4

06:57

2.1 Final Code (for entire section).html

2.2 Starter Code.html

2. 1 - Sorting Customers , Getting our feet wet.mp4

11:38

3. 2 - Comprehensions, Summing, Conditionals.mp4

12:22

4. 3 - datetime module, adding complexity to customers, dictionaries.mp4

11:30

5. 4 - defaultdict, intro to Pandas.mp4

10:26

6. 5 - More Pandas, Introduction to .map.mp4

08:38

2. Applied Problem # 1 - Birthday Paradox

1.1 Colab Notebook.html

1. Birthday Paradox Intro - Reading Data, Sampling.mp4

12:22

2. Applied 1 - Birthday Paradox Solved.mp4

12:20

3. Applied 1 - Birthday Paradox Variations.mp4

15:00

4. Applied 1 - Birthday Outro and Gotcha!.mp4

05:23

3. Natural Language Parsing and Analysis

1.1 Solved Notebook - Use for starter code.html

1.2 Starter Code.html

1. Natural Language Intro and Tokenization.mp4

12:49

2.1 Solved Notebook.html

2.2 Starter Code.html

2. Token Frequencies Solved - Regexp Intro.mp4

10:00

3. Regexp Solved - Using AI to help Code.mp4

12:36

4. %prun performance and Intro to Sentence Similarity Challenge.mp4

13:51

5. Pairwise Sentences Partially Solved - itertools.mp4

10:34

6. Pairwise Sentences Solved - Jaccard Challenge.mp4

12:25

4. Natural Language Project - Using ScikitLearn

1.1 Starter Notebook.html

1. Intro the Section, zip and bigrams + trigrams challenge.mp4

13:16

2. Working with CountVectorizer and the Core idea behind document vector spaces.mp4

13:14

3. Working with numpy and building our own distance metric.mp4

11:49

4. Dot Product, Cosine Similarity and Embeddings.mp4

14:55

5. Pairwise Distances, Numpy Array Indexing and .argminmax.mp4

14:04

6.1 All Solved Code.html

6. Newsgroups Challenge Solved - More on Pandas.mp4

14:59

5. Building Expertise with Pandas and Analyzing Data

1.1 Starter Code.html

1. Parsing the Garmin dataset using beautiful soup.mp4

13:56

2. Converting Points into DataFrame, reviewing comprehensions.mp4

13:28

3. Pandas Type Conversions, Plotting the Workout.mp4

14:58

4. Computing Cumulative Time and analyzing correlations.mp4

14:34

5. Pairplots using Seaborn and Using AI to help us compute cumulative distance.mp4

12:45

6. Using Scipy to find Peaks and Troughs - continuing to code with AI.mp4

14:48

7. Battling through to get the correct peaks and troughs indicated in our dataframe.mp4

14:59

8.1 FINAL NOTEBOOK.html

8. Avg Lap Distance and Also computing total climbing using AI and numpy clip.mp4

14:56

Description

Ditch the Fluff, Embrace the Challenge: Master Python for Real-World Data Science and Analytics

What You'll Learn?

Moving beyond basic Python tutorials into solving complex and practical problems
Mastering both Python and Pandas, while being fluent enough to let AI help you solve problems
Parsing natural language, structured data and analyze any kind of data you may encounter in business or research
Develop confidence in problem solving and your ability to think through a problem
Using AI as a Copilot as we get into progressively complex problem solving

Who is this for?

Data Analysts and Data Scientists

Beginner Python Developers that want to develop deeper skills

What You Need to Know?

Understanding the basics of Python

A Google account to use Colab Notebooks

Have some appreciation for problems data scientists and analyst must solve on a daily basis.

More details

Description
Unlock the Power of Python for Real-World Data Science and Analytics
Are you ready to take your Python skills to the next level and tackle real-world data science and analytics challenges? Look no further than "Applied Python for Data Science and Analytics," a comprehensive Udemy course designed to bridge the gap between memorization and practical problem-solving.

In this course, you'll learn from Jeff James, a senior machine learning engineering manager with 15 years of applied data analytics and coding experience, who has also taught at the University of Denver. Andrew will guide you through the complexities of the Python standard library, Pandas, SciPY, and powerful machine learning libraries like scikit-learn, empowering you to solve open-ended problems with confidence.

Throughout the course, you'll dive deep into real-world scenarios, learning how to approach and solve challenges that go beyond the typical "table of contents" style video courses. You'll gain hands-on experience working with diverse datasets, applying advanced analytical techniques, and leveraging the full potential of Python's data science ecosystem.

Whether you're a data analyst, aspiring data scientist, or a developer looking to expand your skill set, this course will equip you with the tools and knowledge you need to excel in the field. You'll learn how to:

- Effectively utilize the Python standard library for data manipulation and analysis
- Harness the power of pandas for efficient data wrangling and exploration
- Apply statistical techniques using SciPY to gain deeper insights from your data
- Implement machine learning algorithms using scikit-learn to solve real-world problems
- Develop a problem-solving mindset to tackle open-ended challenges in data science and analytics

By the end of this course, you'll have a robust portfolio of projects showcasing your ability to apply Python to real-world data science and analytics problems. You'll be ready to take on complex challenges, drive data-driven decision-making, and make a tangible impact in your organization.

Don't miss this opportunity to learn from an experienced industry professional and elevate your Python skills to new heights. Enroll now in "Applied Python for Data Science and Analytics" and unlock your full potential in the world of data science and analytics!
Who this course is for:
Data Analysts and Data Scientists
Beginner Python Developers that want to develop deeper skills

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Howdy! I'm Jeff James. I currently work as a Senior Data Scientist at one of the world's leading ed-tech companies, Quizlet, where I develop data-driven solutions to improve SEO traffic for one of the world's most popular websites. I also have experience as an instructor at the University of Denver. I love teaching and learning. I hope my passion for self-improvement and learning shines through in my courses. I also believe in contextualized learning and would never produce a "boring" course.

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