Introduction to Data Science and Machine Learning (Udemy.com)

Gain hands-on experience and a deep understanding of data science using a proven step-by-step method

( 0 Reviews )

Created by: Robert Dempsey

Produced in 2018

What you will learn

Turn business problems into data questions.
Automate data collection from from files, APIs and more.
Build a complete machine learning system using Docker, PySpark, Elasticsearch and Kibana
Process large volumes of data using Apache Spark.
Understand when and how to apply supervised and unsupervised learning algorithms.
Train a supervised learning model and create predictions.
Index processed data into Elasticsearch
Perform and share a data analysis in a variety of formats including HTML and PDF.
Create an interactive dashboard for data analysis and reporting using Kibana

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Course Description

Gain hands-on experience building a machine learning system and have a complete project you can add to your online data science portfolio, and code you can adapt to just about any machine learning problem you may encounter.

This course is a comprehensive, foundational data science course where you'll learn everything you need to know to get started in data science.

In this course you play the role of a data scientist for an online retailer, tasked with identifying sales trends and predicting future sales. To do that you'll:

Take a business problem and turn it into a data question
Gather and prepare data for modeling
Test different machine learning models and create predictions
Store and visualize the data and your results
Create reports in many formats charty goodness galore!

Along your journey you get hands-on with the latest machine learning with Python has to offer, including:

Python machine learning libraries: Jupyter Notebook, Pandas, PivotTable.js, Scikit-learn, Matplotlib
Docker
Spark (PySpark)
Elasticsearch
Logstash
Kibana

Who this course is for:

Anyone who wants to get hands-on experience with a data science project from start to finish.
People who want to add a complete project to their data science portfolio.

Time: 9h

Instructor Details

Robert Dempsey

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Accomplished software and data engineer with 18+ years of experience designing and developing applications that support business objectives. Have led key initiatives and developed mission-critical applications that contributed $3.4+ million in revenue and cost savings.

Respected leader, able to build highly motivated teams focused on rapidly developing data analytics applications to improve decision making. Keep up-to-date with changes in the industry through authoring data science books, teaching, speaking, and professional development.

Areas of Expertise
Full Lifecycle Application Development
Distributed, Data-Intensive Applications
Strategic / Tactical Planning
Data Engineering and Machine Learning
Product and Project Management