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Introduction to Data Science, Machine Learning & AI using R
Nivå: Foundation
Snittbetyg:
4,46/5 Based on 635 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.
Nyckelfunktioner:
- 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
Du kommer lära dig att:
- Translate business questions into Machine Learning problems to understand what your data is telling you
- Explore and analyse 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 behaviours 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 behaviours 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
Välj den utbildningsform som passar dig bäst
LIVE, LÄRARLEDD
Klassrum och självstudier
- 5-day instructor-led training course
- One-on-one after-course instructor coaching
- Learning Tree end-of-course exam included
- After-course computing sandbox
PREMIUM UTBILDNING
Klassrum, On-demand och självstudier
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
FÖRETAGSINTERN UTBILDNING
Teamträning
- Använd denna eller någon annan utbildning i ditt företag
- Fullskalig programutveckling
- Levereras när, var och hur du vill
- Blandade utbildningsmodeller
- Skräddarsytt innehåll
- Coaching av ett expertteam
Anpassa kurs och innehåll efter teamets behov
Kontakta ossUtveckla dig och ditt team med anpassade eller öppna kurser alternativt e-learning
Learning Tree erbjuder kundanpassad utbildning hos er, öppna kurser i Stockholm, London eller Washington, möjlighet att delta via våra Anywhere centers (Malmö, Göteborg, Linköping, Stockholm eller Borlänge) eller olika former av e-learning med lärarstöd. Läs mer på www.learningtree.se/priser .
Klassrum och självstudier
Note: This course runs for 5 dagar *
*Events with the Partial Day Event clock icon run longer than normal but provide the convenience of half-day sessions.
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3 - 7 aug 9:00 - 4:30 BST London / Online (AnyWare) Boka Din Kursplats
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12 - 16 okt 9:00 - 4:30 BST London / Online (AnyWare) Boka Din Kursplats
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14 - 18 dec 9:00 - 4:30 GMT London / Online (AnyWare) Boka Din Kursplats
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1 - 5 feb 9:00 - 4:30 GMT London / Online (AnyWare) Boka Din Kursplats
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12 - 16 apr 9:00 - 4:30 BST London / Online (AnyWare) Boka Din Kursplats
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15 - 19 jun 9:00 - 4:30 EDT Online (AnyWare) Boka Din Kursplats
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24 - 28 aug 9:00 - 4:30 EDT Toronto / Online (AnyWare) Boka Din Kursplats
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31 aug - 4 sep 9:00 - 4:30 EDT Ottawa / Online (AnyWare) Boka Din Kursplats
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14 - 18 sep 9:00 - 4:30 EDT Herndon, VA / Online (AnyWare) Boka Din Kursplats
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28 sep - 2 okt 9:00 - 4:30 EDT Alexandria, VA / Online (AnyWare) Boka Din Kursplats
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16 - 20 nov 9:00 - 4:30 EST New York / Online (AnyWare) Boka Din Kursplats
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8 - 12 feb 9:00 - 4:30 EST Toronto / Online (AnyWare) Boka Din Kursplats
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1 - 5 mar 9:00 - 4:30 EST Ottawa / Online (AnyWare) Boka Din Kursplats
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15 - 19 mar 9:00 - 4:30 EDT Herndon, VA / Online (AnyWare) Boka Din Kursplats
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29 mar - 2 apr 9:00 - 4:30 EDT Alexandria, VA / Online (AnyWare) Boka Din Kursplats
Kurs med startgaranti
När du ser symbolen för “Guaranteed to Run” vid ett kurstillfälle vet du att kursen blir av. Garanterat.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
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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.
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Recommended Experience
There's no expectations regarding specific platforms except basic familiarity with a Windows environment.
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Who Should Attend this Data Science Training
It’s designed for beginners, technical and non-technical.
Introduction to Data Science Course Outline
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Introduction to R
Exploratory Data Analysis with R
- Loading, querying and manipulating data in R
- Cleaning raw data for modelling
- Reducing dimensions with Principal Component Analysis
- Extending R with user–defined packages
Facilitating good analytical thinking with data visualisation
- Investigating characteristics of a data set through visualisation
- Charting data distributions with boxplots, histograms and density plots
- Identifying outliers in data
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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
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Predicting Outcomes with Regression Techniques
Estimating future values with linear regression
- Modelling 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’
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Categorising 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
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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
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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
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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 modelling
- Analysing labelled data examples to find patterns in those examples that consistently correlate with particular labels for object recognition
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Implementing Analytics within Your Organisation
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
- Visualising data to tell a story
Data Science FAQs
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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 specialised or technical knowledge prior to attendance.
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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.
Klassrum, On-demand och självstudier
Note: This course runs for 5 dagar *
*Events with the Partial Day Event clock icon run longer than normal but provide the convenience of half-day sessions.
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3 - 7 aug 9:00 - 4:30 BST London / Online (AnyWare)
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12 - 16 okt 9:00 - 4:30 BST London / Online (AnyWare)
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14 - 18 dec 9:00 - 4:30 GMT London / Online (AnyWare)
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1 - 5 feb 9:00 - 4:30 GMT London / Online (AnyWare)
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12 - 16 apr 9:00 - 4:30 BST London / Online (AnyWare)
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15 - 19 jun 9:00 - 4:30 EDT Online (AnyWare)
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24 - 28 aug 9:00 - 4:30 EDT Toronto / Online (AnyWare)
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31 aug - 4 sep 9:00 - 4:30 EDT Ottawa / Online (AnyWare)
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14 - 18 sep 9:00 - 4:30 EDT Herndon, VA / Online (AnyWare)
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28 sep - 2 okt 9:00 - 4:30 EDT Alexandria, VA / Online (AnyWare)
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16 - 20 nov 9:00 - 4:30 EST New York / Online (AnyWare)
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8 - 12 feb 9:00 - 4:30 EST Toronto / Online (AnyWare)
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1 - 5 mar 9:00 - 4:30 EST Ottawa / Online (AnyWare)
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15 - 19 mar 9:00 - 4:30 EDT Herndon, VA / Online (AnyWare)
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29 mar - 2 apr 9:00 - 4:30 EDT Alexandria, VA / Online (AnyWare)
Kurs med startgaranti
När du ser symbolen för “Guaranteed to Run” vid ett kurstillfälle vet du att kursen blir av. Garanterat.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.Data Science Obegränsad åtkomst kursinformation
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 (1253) course events.
Utbildningsplan On-Demand
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On-Demand Courses
- R Data Analysis Solutions – Machine Learning Techniques
- Getting Started with Neural Nets in R
- Advanced Machine Learning with R
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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
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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.
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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.
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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.
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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 practise as you read and watch.
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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.
Teamträning
Your Training Comes with a 100% Satisfaction Guarantee!*
*Partner-delivered courses may have different terms that apply. Ask for details.