Python for Data Science and Machine Learning Bootcamp

Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!
4.62 (151673 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Python for Data Science and Machine Learning Bootcamp
769 994
students
25 hours
content
May 2020
last update
$119.99
regular price

Why take this course?

🚀 Python for Data Science and Machine Learning Bootcamp 📘


🎯 Course Headline:

Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more!


🚀 Course Description:

Are you ready to embark on an exciting journey into the world of Data Science? 🚂 With the demand for data scientists skyrocketing and the field consistently ranked as one of the most coveted and highest-paid careers, now is the perfect time to dive in! 💼✨

Data Scientist has been crowned the number one job on Glassdoor, and with an average salary of over $120,000 in the United States according to Indeed, it's no wonder why. Data Science offers a unique blend of analytical skills, programming expertise, and problem-solving that can tackle some of the most pressing issues we face today. 🌍

Whether you're a complete beginner with some programming experience or an experienced developer aspiring to transition into the realm of Data Science, this course is tailored for you! 👩‍💻👨‍💻


✨ What You'll Learn:

This bootcamp-style course is packed with over 100 HD video lectures and detailed code notebooks for every lecture, making it one of the most comprehensive online courses available on Udemy for data science and machine learning! 🎥📚

Here's a sneak peek into what you'll master:

  • Programming with Python to lay down your foundation.
  • NumPy with Python to handle large arrays and matrices efficiently.
  • Mastering pandas Data Frames to manipulate data like a pro.
  • Handling Excel files with pandas, making you the go-to person for data analysis.
  • Web scraping with Python to collect valuable datasets from the web.
  • Connecting Python to SQL databases for robust data storage and retrieval.
  • Creating stunning data visualizations with matplotlib and seaborn.
  • Crafting interactive visualizations with Plotly.
  • Diving into Machine Learning with SciKit Learn, covering a wide range of models:
    • Linear Regression, K Nearest Neighbors, K Means Clustering, Decision Trees, Random Forests.
    • Exploring the world of Natural Language Processing to understand and manipulate human language.
    • Delving into Neural Nets and Deep Learning for complex pattern recognition.
    • Mastering Support Vector Machines (SVM).
  • Plus, much more! 🧙‍♂️✨

📆 Enrollment Details:

Join Jose Portillas in this transformative learning experience that can kickstart your career as a Data Scientist. With the knowledge and skills you'll gain from this course, you'll be equipped to analyze data, create visualizations, and deploy machine learning models with confidence. 🎓

Don't miss out on this opportunity! Enroll in the course today and take your first step towards becoming a Data Science expert. 🚀


Enroll now and let's transform data into actionable insights and innovative solutions! 🌟

Course Gallery

Python for Data Science and Machine Learning Bootcamp – Screenshot 1
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Python for Data Science and Machine Learning Bootcamp – Screenshot 2
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Comidoc Review

Our Verdict

Python for Data Science and Machine Learning Bootcamp offers an extensive overview of various Python libraries, enabling learners to gain hands-on experience in data science. While some minor issues exist with the exercise solution notebooks and library version changes, this course is still valuable due to its clear explanations, real-life examples, and updated course materials.

What We Liked

  • In-depth coverage of various Python libraries for data science
  • Clear explanations and real-life examples provided by the instructor
  • Hands-on exercises to practice concepts taught in each section
  • Updated course materials, including recent changes in software

Potential Drawbacks

  • Some exercise solution notebooks contain errors or outdated code
  • Notebook updates are not regularly performed to reflect library version changes
  • Inadequate focus on deep learning section and Spark integration
  • Lack of in-depth discussions on certain topics, such as regularization
903744
udemy ID
13/07/2016
course created date
14/05/2019
course indexed date
Bot
course submited by