Python for Machine Learning

Price
$1,895.00 USD

Duration
2 Days

 

Delivery Methods
Virtual Instructor Led
Private Group

Course Overview

Master the skills to use machine learning in your day-to-day work with this Python course. Create algorithms to predict classes, continuous values, and more.

This course is designed for the student who already knows some Python and is ready to dive deeper into using those Python skills for Machine Learning. With a focus on SciKit Learn, you’ll learn all aspects of Machine Learning ranging from a variety of regression types (Linear / Lasso /Ridge), Elastic Net, K Nearest Neighbors and Means Clustering, Hierarchal Clustering, DBSCAN, PCA, and Model Deployment.

This course includes 6-months access to the full course content in on-demand format to support post-class reference and review.

Course Objectives

  • You will learn how to use data science and machine learning with Python.
  • Understand Machine Learning from top to bottom.
  • Learn NumPy for numerical processing with Python.
  • Conduct feature engineering on real world case studies.
  • Learn Pandas for data manipulation with Python.
  • Create supervised machine learning algorithms to predict classes.
  • Create regression machine learning algorithms for predicting continuous values.
  • Construct a modern portfolio of machine learning resume projects.
  • Learn how to use Scikit-learn to apply powerful machine learning algorithms.
  • Get set-up quickly with the Anaconda data science stack environment.
  • Understand the full product workflow for the machine learning lifecycle.
  • Explore how to deploy your machine learning models as interactive APIs.

Who Should Attend?

Experienced Python developers looking to understand a wide variety of machine learning algorithms, including supervised and unsupervised learning algorithms.
  • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
  • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
  • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
  • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
  • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
  • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

Learning Credits: Learning Credits can be purchased well in advance of your training date to avoid having to commit to specific courses or dates. Learning Credits allow you to secure your training budget for an entire year while eliminating the administrative headache of paying for individual classes. They can also be redeemed for a full year from the date of purchase. If you have previously purchased a Learning Credit agreement with New Horizons, you may use a portion of your agreement to pay for this class.

Corporate Tech Pass: Our Corporate Tech Pass includes unlimited attendance for a single person, in the following Virtual Instructor Led course types: Microsoft Office, Microsoft Technical, CompTIA, Project Management, SharePoint, ITIL, Certified Ethical Hacker, Certified Hacking Forensics Investigator, Java, Professional Development Courses and more. The full list of eligible course titles can be found at https://www.newhorizons.com/eligible.

If you have questions about Learning Credits or our Corporate Tech Pass, please contact your Account Manager.

Course Prerequisites

To be successful in this course, learners should have the following: Intermediate Python skills and knowledge
  • Level of knowledge and experience gained from Python for Data Science
  • Agenda

    • Python
    • Jupyter notebooks
    • Numpy
    • Pandas
    • Matplotlib
    • Machine Learning concepts
    • Supervised vs Unsupervised Learning
    • Types of Machine Learning – Classification vs Regression
    • Evaluation
    • Machine Learning Methods – All in Theory and Practice
    • Linear Regression
    • Logistic Regression
    • K Nearest Neighbors
    • Support Vector Machine
    • Decision Trees
    • Unsupervised Learning Methods
    • Feature Engineering and Data Preparation
     

    Upcoming Class Dates and Times

    Mar 18,19
    10:00 AM - 6:00 PM
    ENROLL $1,895.00 USD
    Jun 3,4
    10:00 AM - 6:00 PM
    ENROLL $1,895.00 USD
    Sep 23,24
    10:00 AM - 6:00 PM
    ENROLL $1,895.00 USD
     



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