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Python for Machine Learning

Python for Machine Learning is a foundational course for learning the core details of Numpy, Pandas, Plotly, and Scikit Learn. In the process you will explore the essentials of machine learning by building your own supervised and unsupervised learning algorithms for business analytics and reporting. At the end of the course you will have built a portfolio of data science and machine learning applications that you can reference or share with your team and colleagues using Streamlit in combination with HuggingFace.

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Armando Banuelos
Software Engineer & Educator
Price
US$ 300
or included with membership
Duration
4 weeks
Space is limited

Course taught by expert instructors

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Armando Banuelos

Software Engineer & Educator

Armando Banuelos is a seasoned software engineer with a passion for driving technological advancements. Previously, he served as a Software Engineer at the Chan Zuckerberg Initiative, where he contributed to groundbreaking projects impacting K12 education around the world. Previously, Armando was a Software Engineer at IBM, and has been involved in cutting-edge education throughout his career as a Machine Learning Course Developer at Stanford University. Armando holds a Bachelor's degree in Computer Science from Stanford University and a Master's degree in Computer Science from Georgia Tech.

The course

Learn and apply skills with real-world projects.

Who is it for?
  • Anyone with some programming knowledge interested in becoming a Data Analyst, Data Scientist or Machine Learning Engineer.

  • Software Engineers skilled in programming looking for a career change into data science.

  • Financial Analysts, Accountants, or other professionals looking to learn Python for powerful analysis.

Prerequisites
  • Comfort with Python fundamentals (as covered in Uplimit's Python Crash Course) - variables, functions, lists, loops, dictionaries

Not ready?

Try these prep courses first

Learn
  • File Input/Output
  • Computation on arrays
  • Aggregation
  • Slicing, indexing, and modifying arrays
Project
  • Use Numpy to perform fast calculations and make comparisons with plain Python. This means you will calculate the distance between your location and that of Airbnb listings, and make use of Streamlit to visualize these measurements.
Learn
  • Pandas data structures
  • Operating on data in Pandas
  • Handling missing data
  • Combining datasets
Project
  • Cleaning and generally preprocessing data is a typical task where you need Pandas. This you will learn this week. At the end the results are wrapped up and packages as another Streamlit project.
Learn
  • Plotly data visualizations
  • How to train machine learning models
  • Splitting data into training, validation, and testing sets
  • Feature selection
  • Decision Trees
Project
  • Use numpy and pandas to pre-process training and testing data. Use scikit-learn linear regression supervised learning to predict the price of Airbnb by training on various features.
Learn
  • Exploration of supervised and unsupervised machine learning algorithms in scikit-learn
  • Scikit-learn machine learning pipelines
Project
  • Implement a K-Means clustering unsupervised learning algorithm to identify groupings across Airbnb listings and also use Support Vector Machines (SVM) for Airbnb classification.

A course you'll actually complete. AI-powered learning that drives results.

AI-powered learning

Transform your learning programs with personalized learning. Real-time feedback, hints at just the right moment, and the support for learners when they need it, driving 15x engagement.

Live courses by leading experts

Our instructors are renowned experts in AI, data, engineering, product, and business. Deep dive through always-current live sessions and round-the-clock support.

Practice on the cutting edge

Accelerate your learning with projects that mirror the work done at industry-leading tech companies. Put your skills to the test and start applying them today.

Flexible schedule for busy professionals

We know you’re busy, so we made it flexible. Attend live events or review the materials at your own pace. Our course team and global community will support you every step of the way.

Timeline

Completion certificates

Each course comes with a certificate for learners to add to their resume.

Best-in-class outcomes

15-20x engagement compared to async courses

Support & accountability

You are never alone, we provide support throughout the course.

Get reimbursed by your company

More than half of learners get their Courses and Memberships reimbursed by their company.

Hundreds of companies have dedicated L&D and education budgets that have covered the costs.

Reimbursement

Frequently Asked Questions

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