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Professional Course

From 0 to 1: Machine Learning, NLP & Python-Cut to the Chase

QuickStart, Online
Length
7 hours
Price
44.99 USD
Next course start
Start anytime! See details
Delivery
Self-paced Online
Length
7 hours
Price
44.99 USD
Next course start
Start anytime! See details
Delivery
Self-paced Online
This provider usually responds within 48 hours 👍

Course description

From 0 to 1: Machine Learning, NLP & Python-Cut to the Chase

About this course:

First, let’s get the idea about what Machine Learning, NLP and Python is. Well for starters, Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. Neuro-linguistic programming (NLP) is an approach to communication, personal development, and psychotherapy created by Richard Bandler and John Grinder in California, United States in the 1970s.

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. In this course students will learn about Machine Learning, Natural Language Processing with Python, Sentiment Analysis, Mitigating Overfitting with Ensemble Learning.

The average salary for Big Data Professional is $69,870 per year.

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Upcoming start dates

1 start date available

Start anytime!

  • Self-paced Online
  • Online

Who should attend?

Audience: 

This course is intended for:

  • Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning
  • Engineers who want to understand or learn machine learning and apply it to problems they are solving

Prerequisites:

  • No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

Training content

Course Objective:

After completing this course, students will have a working understanding of:

  • Solving Classification Problems
  • Clustering as a form of Unsupervised learning
  • Association Detection
  • Dimensionality Reduction
  • Regression as a form of supervised learning
  • Natural Language Processing and Python
  • Sentiment Analysis
  • Decision Trees
  • A Few Useful Things to Know About Overfitting
  • Random Forests
  • Recommendation Systems

Quick stats about QuickStart?

98% increased workplace productivity

94% instructor and course effectiveness

Partnered with vendors including Microsoft, Cisco, and Citrix

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QuickStart
1101 S Capital of Texas Hwy - Building J, Suite 202
78746 Austin Texas

Meet your career goals with QuickStart!

QuickStart exists to create world-class technologists by personalizing and individualizing training to address the massive skills gap in the IT industry. Through 20 years of research and data analysis, we’ve learned that a modern learner prefers to learn through multiple...

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