Practical Data Science and Machine Leaning

  • Overview
  • Course Content
  • Requirements & Materials
Overview

Practical Data Science and Machine Leaning

Course Description

This class if for engineers who are not professional software developers but need an understanding of modern tooling required to efficiently process and learn from data. You will be introduced to the tools, theory, and methods for working with applied data science and machine learning (DS/ML). As a project based class, you will be guided through a series of practical data science problems and learn how to use and interact with open source DS/ML tools, the theory behind canonical ML algorithms, and practical methods and workflows for learning from data.

Course Content

DEVOPS FOR DATA SCIENCE

  • Efficiently integrate with Google, Amazon, and Azure Cloud products to create remote and
  • repeatable computing environments
  • Linux command line fundamentals for installing and maintaining production enterprise
  • DS/ML pipelines

DATA SCIENCE BASICS IN PYTHON

  • How to install Jupyter and how to use it on remote machines
  • Deep dive into data manipulation with Pandas and Numpy
  • Data visualization theory and practice using Matplotlib and Seaborn

MACHINE LEARNING THEORY

  • Introduction and review of ML theory and algorithms
  • Supervised learning, unsupervised learning, ensemble methods, boosting, deep neural networks

MACHINE LEARNING PRACTICE

  • Classical ML techniques and conventions using Scikit-Learn
  • Deep neural network learning using Tensorflow and Keras

SCALING DATA PIPELINES

  • Processing big data with Hadoop and PySpark
  • Creating repeatable production batch job pipelines using Luigi
Requirements & Materials

Requirements

Provided

  • Soft copies of course material emailed to all learners

Who Should Attend

This course is designed for engineers, scientists, and managers from commercial industry, educational institutions, and government agencies. A core toolset will be covered that is relevant to skills across almost any modern industry, from science to advertising to industrial automation.

What You Will Learn

  • Modern developer tools
  • Data science workflow
  • Data science with Python in a browser
  • Manipulating data in Python
  • Visualization stories with data
  • Machine learning theory
  • Machine learning workflow and pipelines
  • How to deal with bigger data

How You Will Benefit

  • Implement fully functioning machine learning pipelines.
  • Apply modern DS/ML toolchain to practical problems.
  • Become a proficient user of Python and Jupyter.
  • Implement data visualization for effective data storytelling.
  • Apply big data tools, such as Hadoop, Spark, and Amazon Web Services to data problems.
  • Taught by Experts in the Field icon
    Taught by Experts in the Field
  • Grow Your Professional Network icon
    Grow Your Professional Network

The course schedule was well-structured with a mix of lectures, class discussions, and hands-on exercises led by knowledgeable and engaging instructors.

- Abe Kani
President

TRAIN AT YOUR LOCATION

We enable employers to provide specialized, on-location training on their own timetables. Our world-renowned experts can create unique content that meets your employees' specific needs. We also have the ability to deliver courses via web conferencing or on-demand online videos. For 15 or more students, it is more cost-effective for us to come to you.

  • Save Money
  • Flexible Schedule
  • Group Training
  • Customize Content
  • On-Site Training
  • Earn a Certificate
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