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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.
There's no expectations regarding specific platforms except basic familiarity with a Windows environment.
It’s designed for beginners, technical and non-technical.
Exploratory Data Analysis with R
Facilitating good analytical thinking with data visualization
Mining unstructured data for business applications
Estimating future values with linear regression
Automating the labelling of new data items
Assessing model performance
Identifying previously unknown groupings within a data set
Discovering connections with Link Analysis
Building and evaluating association rules
Constructing recommendation engines
Machine learning with neural networks
Expanding analytic capabilities
Dissemination and Data Science policies
Course Tuition Includes:
After-Course Instructor Coaching
When you return to work, you are entitled to schedule a free coaching session with your instructor for help and guidance as you apply your new skills.
After-Course Computing Sandbox
You'll be given remote access to a preconfigured virtual machine for you to redo your hands-on exercises, develop/test new code, and experiment with the same software used in your course.
Free Course Exam
You can take your Learning Tree course exam on the last day of your course or online at any time after class and receive a Certificate of Achievement with the designation "Awarded with Distinction."
Standard Course Hours:9:00 am – 4:30 pm
FREE Online Course Exam (if applicable) – Last Day:3:30 pm – 4:30 pm
By successfully completing your FREE online course exam, you will:
Each Course Day - Informal discussion with instructor about your projects or areas of special interest:4:30 pm – 5:30 pm