Introduction to Data Science and Machine Learning

Learning Tree International

Price:
$3,190
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Location:
Downtown, Washington, D.C.
1110 Vermont Ave NW Ste 700
Btwn L NW & M NW Streets
Washington, District of Columbia 20005
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Course 1253
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Class Level: Beginner
Age Requirements: 18 and older
Average Class Size: 16

What you'll learn in this business intelligence training:

If you want to become a data scientist, this is the course to begin with. 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, this course will give you the foundation you need to assess which options best suit your needs.

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

Who Should Attend: It’s designed for beginners, technical and non-technical.

Course Outline:
  • Introduction to R
  • Working with Unstructured Data
  • Predicting Outcomes with Regression Techniques
  • Categorizing Data with Classification Techniques
  • Detecting Patterns in Complex Data with Clustering and Social Network Analysis
  • Leveraging Transaction Data to Yield Recommendations and Association Rules
  • Learning from Data Examples with Neural Networks
  • Implementing Analytics within Your Organization

Still have questions? Ask the community.

If a customer would like to cancel or transfer their course, they must notify Coursehorse prior to two weeks before the start date of the course or within seven days of registration. On-Demand Courses cannot be cancelled once purchased and are not eligible for refund.

If a customer transfers to another course prior to two weeks before the start date or within seven days of registration of the course in which originally enrolled, 100% of any prepaid course tuition will be applied toward the course tuition for the subsequent course.

If a customer needs to cancel an enrollment two weeks prior to the start of the class or within seven days of registration, we will refund 100% of any prepaid course tuition for that enrollment.

If a customer does need to transfer or cancel a course within two weeks of the start date of the course or after seven days from the date of registration, a fee equal to 50% of the price of the course will be assessed for any standard attendances. Attendances associated with a Learning Tree program will be assessed a $500 fee. Training Passports, Training Vouchers and Pay-As-You-Learn Vouchers cannot be used after their expiration dates, and a course cancellation or transfer by the customer will not extend a Training Passport, Training Voucher Pack or Pay-As-You-Learn Voucher Pack expiration date.

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School: Learning Tree International

Learning Tree International

Established in 1974, Learning Tree International is a leading provider of IT training and management training to business and government organizations worldwide. In addition, Learning Tree provides IT Workforce Optimization Solutions – a modern approach that improves the adoption of skills, and accelerates...

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