Introduction to Data Science, Machine Learning & AI using R

Level: Foundation
Rating: 4.5/5 4.47/5 Based on 602 Reviews

If you want to become a data scientist, this Introduction to Data Science is the course to get you startetd. Using open source tools, it covers all the concepts necessary to move through the entire data science pipeline, and whether you intend to continue working with open source tools, or later opt for proprietary services, it will give you the foundation you need to assess which options best suit your needs.

Attend this Data Science training in one of three formats - live, instructor-led, blended on-demand/instructor-led, or train your whole team by bringing this course to your facility.

Introduction to Data Science, Machine Learning & AI using R

Key Features of this Introduction to Data Science Training:

  • Choose from blended on-demand and instructor-led learning options
  • Exclusive LinkedIn group membership for peer and SME community support
  • After-course instructor coaching benefit
  • Learning Tree end-of-course exam included
  • After-course computing sandbox included

You Will Learn How To:

  • Translate business questions into Machine Learning problems to understand what your data is telling you
  • Explore and analyze data from the Web, Word Documents, Email, Twitter feeds, NoSQL stores, Relational Databases and more, for patterns and trends relevant to your business
  • Build Decision Tree, Logistic Regression and Naïve Bayes classifiers to make predictions about your customers’ future behaviors as well as other business critical events
  • Use K-Means and Hierarchical Clustering algorithms to more effectively segment your customer market or to discover outliers in your data
  • Discover hidden customer behaviors from Association Rules and Build Recommendation Engines based on behavioral patterns
  • Use biologically-inspired Neural Networks to learn from observational data as humans do
  • Investigate relationships and flows between people, computers and other connected entities using Social Network Analysis

Choose the Data Science Training Solution that Best Fits Your Individual Needs or Organizational Goals

LIVE, INSTRUCTOR-LED

In Class & Live, Online Training

  • 5-day instructor-led training course
  • One-on-one after-course instructor coaching
  • Learning Tree end-of-course exam included 
  • After-course computing sandbox
View Course Details & Schedule

Standard $3710

Government $3260

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PRODUCT #1253

PREMIUM TRAINING

Unlimited Access to Everything

Unlimited annual access to:

  • 3 on-demand courses
  • 5 eBooks
  • 5-day instructor-led training course
  • One-on-one after-course instructor coaching
  • After-course computing sandbox included 
  • Learning Tree end-of-course exam included
View Bundle Details & Schedule

Standard $4275/Year

Government $4275/Year

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PRODUCT #70G8

TRAINING AT YOUR SITE

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  • Bring this or any training to your organization
  • Full - scale program development
  • Delivered when, where, and how you want it
  • Blended learning models
  • Tailored content
  • Expert team coaching

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Save More On Training with FlexVouchers – A Unique Training Savings Account

Our FlexVouchers help you lock in your training budgets without having to commit to a traditional 1 voucher = 1 course classroom-only attendance. FlexVouchers expand your purchasing power to modern blended solutions and services that are completely customizable. For details, please call 888-843-8733 or chat live.

In Class & Live, Online Training

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Note: This course runs for 5 Days *

*Events with the Partial Day Event clock icon run longer than normal but provide the convenience of half-day sessions.

  • Oct 5 - 9 9:00 AM - 4:30 PM PDT Online (AnyWare) Online (AnyWare) Reserve Your Seat

  • Nov 16 - 20 9:00 AM - 4:30 PM EST Online (AnyWare) Online (AnyWare) Reserve Your Seat

  • Dec 7 - 11 9:00 AM - 4:30 PM EST Online (AnyWare) Online (AnyWare) Reserve Your Seat

  • Feb 8 - 12 9:00 AM - 4:30 PM EST Toronto / Online (AnyWare) Toronto / Online (AnyWare) Reserve Your Seat

  • Mar 1 - 5 9:00 AM - 4:30 PM EST Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

  • Mar 15 - 19 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

  • May 17 - 21 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

  • Jul 26 - 30 9:00 AM - 4:30 PM EDT Toronto / Online (AnyWare) Toronto / Online (AnyWare) Reserve Your Seat

  • Aug 30 - Sep 3 9:00 AM - 4:30 PM EDT Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

  • Sep 13 - 17 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

Guaranteed to Run

When you see the "Guaranteed to Run" icon next to a course event, you can rest assured that your course event — date, time — will run. Guaranteed.

Partial Day Event

Learning Tree offers a flexible schedule program. If you cannot attend full day sessions, this option consists of four-hour sessions per day instead of the full-day session.

Important Introduction to Data Science Course Information

  • Introduction to Data Science Training Course Description

    This Data Science, Machine Learning & AI training course includes 29 hours of Instructor-Led Training (ILT) or Virtual Instructor-Led Training (VILT) presented by a real-world data science expert. Attend in-person or online through our AnyWare virtual training platform.

  • Recommended Experience

    There's no expectations regarding specific platforms except basic familiarity with a Windows environment.

  • Who Should Attend this Data Science Training

    It’s designed for beginners, technical and non-technical.

Introduction to Data Science Course Outline

  • Introduction to R

    Exploratory Data Analysis with R

    • Loading, querying and manipulating data in R
    • Cleaning raw data for modeling
    • Reducing dimensions with Principal Component Analysis
    • Extending R with user–defined packages

    Facilitating good analytical thinking with data visualization

    • Investigating characteristics of a data set through visualization
    • Charting data distributions with boxplots, histograms and density plots
    • Identifying outliers in data
  • Working with Unstructured Data

    Mining unstructured data for business applications

    • Preprocessing unstructured data in preparation for deeper analysis
    • Describing a corpus of documents with a term–document matrix
    • Make predictions from textual data
  • Predicting Outcomes with Regression Techniques

    Estimating future values with linear regression

    • Modeling the numeric relationship between an output variable and several input variables
    • Correctly interpreting coefficients of continuous data
    • Assess your regression models for ‘goodness of fit’
  • Categorizing Data with Classification Techniques

    Automating the labelling of new data items

    • Predicting target values using Decision Trees
    • Constructing training and test data sets for predictive model building
    • Dealing with issues of overfitting

    Assessing model performance

    • Evaluating classifiers with confusion matrices
    • Calculating a model’s error rate
  • Detecting Patterns in Complex Data with Clustering and Social Network Analysis

    Identifying previously unknown groupings within a data set

    • Segmenting the customer market with the K–Means algorithm
    • Defining similarity with appropriate distance measures
    • Constructing tree–like clusters with hierarchical clustering
    • Clustering text documents and tweets to aid understanding

    Discovering connections with Link Analysis

    • Capturing important connections with Social Network Analysis
    • Exploring how social networks results are used in marketing
  • Leveraging Transaction Data to Yield Recommendations and Association Rules

    Building and evaluating association rules

    • Capturing true customer preferences in transaction data to enhance customer experience
    • Calculating support, confidence and lift to distinguish "good" rules from "bad" rules
    • Differentiating actionable, trivial and inexplicable rules

    Constructing recommendation engines

    • Cross–selling, up–selling and substitution as motivations
    • Leveraging recommendations based on collaborative filtering
  • Learning from Data Examples with Neural Networks

    Machine learning with neural networks

    • Learning the weight of a neuron
    • Learning about how neural networks are being applied to object recognition, image segmentation, human motion and language modeling
    • Analyzing labelled data examples to find patterns in those examples that consistently correlate with particular labels for object recognition
  • Implementing Analytics within Your Organization

    Expanding analytic capabilities

    • Breaking down Data Analytics into manageable steps
    • Integrating analytics into current business processes
    • Reviewing Hadoop, Spark, and Azure services for machine learning

    Dissemination and Data Science policies

    • Examining ethical questions of privacy in Data Science
    • Disseminating results to different types of stakeholders
    • Visualizing data to tell a story

Data Science FAQs

  • Is this a good starting point for how to become a data scientist?

    Yes, this course is designed as an introduction to data science, machine learning, and AI, and does not require any specialized or technical knowledge prior to attendance.

  • Can I take this data science course online?

    Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient online training to meet your needs wherever you want, including online training.

Unlimited Access to Everything

Time Zone Legend:
Eastern Time Zone Central Time Zone
Mountain Time Zone Pacific Time Zone

Note: This course runs for 5 Days *

*Events with the Partial Day Event clock icon run longer than normal but provide the convenience of half-day sessions.

  • Oct 5 - 9 9:00 AM - 4:30 PM PDT Online (AnyWare) Online (AnyWare)

  • Nov 16 - 20 9:00 AM - 4:30 PM EST Online (AnyWare) Online (AnyWare)

  • Dec 7 - 11 9:00 AM - 4:30 PM EST Online (AnyWare) Online (AnyWare)

  • Feb 8 - 12 9:00 AM - 4:30 PM EST Toronto / Online (AnyWare) Toronto / Online (AnyWare)

  • Mar 1 - 5 9:00 AM - 4:30 PM EST Ottawa / Online (AnyWare) Ottawa / Online (AnyWare)

  • Mar 15 - 19 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare)

  • May 17 - 21 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) New York / Online (AnyWare)

  • Jul 26 - 30 9:00 AM - 4:30 PM EDT Toronto / Online (AnyWare) Toronto / Online (AnyWare)

  • Aug 30 - Sep 3 9:00 AM - 4:30 PM EDT Ottawa / Online (AnyWare) Ottawa / Online (AnyWare)

  • Sep 13 - 17 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare)

Guaranteed to Run

When you see the "Guaranteed to Run" icon next to a course event, you can rest assured that your course event — date, time — will run. Guaranteed.

Partial Day Event

Learning Tree offers a flexible schedule program. If you cannot attend full day sessions, this option consists of four-hour sessions per day instead of the full-day session.

Introduction to Data Science Unlimited Access Training Information

  • Course Description

    This product offers access to 3 on-demand courses and 5 eBooks that have been mapped directly to the objectives of the 5-day course. Enrolling in this bundle also grants you access to any of our multi-day Introduction to Data Science, Machine Learning & AI (Course 1253) course events.

  • How to Schedule Your Instructor-Led Training

    Once payment is received, you will receive details for your Unlimited Access Training Bundle via email. At that time, you may call or email our customer service team for assistance in enrolling in the event date of your choice.

On-Demand Training Content

  • On-Demand Courses

    • R Data Analysis Solutions – Machine Learning Techniques
    • Getting Started with Neural Nets in R
    • Advanced Machine Learning with R
  • eBooks

    • Machine Learning with Algorithims – 2nd Edition
    • Mastering Machine Learning with R – 2nd Edition
    • Data Analysis with R – 2nd Edition
    • R Programming Fundamentals
    • Modern R Programming Cookbook

Data Science Training FAQs

  • What background do I need for this Data Science training?

    There's no expectations regarding specific platforms except basic familiarity with a Windows environment. It’s designed for beginners, technical and non-technical.

  • Is the on-demand content the same as the 5-day instructor class?

    No. While the content selected does map to the objectives of the instructor-led course, it does not include a recorded version of the instructor-led class. The objectives have been re-imagined to be presented in digital, self-guided formats.

  • What on-demand content will I receive?

    An outline of the content you will receive can be seen above. You will also get access to any new on-demand content that becomes available during your annual enrolment period.

  • Does this include any practical, hands-on learning?

    Yes! Each book and video begins with a step by step guide for you to set up a coding environment on your personal computer. The course content is full of examples and practical advice, followed up by the chance to embed your learning through real world tasks. All example code is available to download, copy and use - giving you the chance to work and practice as you read and watch.

  • How will I access my course materials if I choose this method?

    Once payment is received, you will receive an email from Learning Tree with all the links and information you need to get started.

  • How do I schedule my instructor-led training?

    Once payment is received, you will receive details for your Unlimited Access Training Bundle via email. At that time, you may call or email our customer service team for assistance in enrolling in the event date of your choice.

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