Dates and location
Pricing
Hours
Dates and location
Pricing
Hours
Description
This intensive, online learning experience will lay the groundwork for your journey to becoming data scientist. Learn essential data science skills directly from industry thought leaders. From sourcing and preparing data to analytic modelling and delivering insights, the bootcamp provides a complete overview of what it takes to succeed as a data scientist. Learn through case studies that illustrate the work of data science in real-life businesses.
The course is divided into four topics:
1. Overview of Data Science with Dean Abbott, SmarterHQ Inc.
2. Data Sourcing and Preparation for Data Science with William Henry, Henry Analytics
3. Modelling Your Data: Building and Assessing Models with Natasha Balac, PhD University of California at San Diego
4. Data Science in the Enterprise with John Akred, Silicon Valley Data Science
LEARNING OBJECTIVES
Overview of Data Science
- Understand the skills and education needed to become data scientist
- Define data science and understand the marketplace demand
- Categorize data science work into six main areas
Data Sourcing and Preparation for Data Science
- Understand data collection, description, exploration and quality verification
- Describe data preparation including selection, cleansing and construction
- Identify how data is integrated, formatted and stored
Modelling Your Data: Building and Assessing Models
- Build and assess predictive models
- List modelling methods such as decision tree, regression tree and clustering
- Understand the history and terminology of data mining
Data Science in the Enterprise
- Understand what it takes to build a data-driven culture
- Define data science techniques and methods for running data science projects
- List the types of tools and platforms available in the marketplace
WHO WILL BENEFIT
Data quality and data governance professionals; business intelligence (BI) and data warehouse (DW) managers, designers, and developers; and anyone with a role in data quality or information systems testing.
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How to Access The Course
This is an online session. This course is available 24 hours a day, 7 days a week. Once registered, you can access the material at any time.
However, you will only have access to the course for 90 days after REGISTRATION.
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To access the course on your computer please visit our BlackBoard site, and log-in using the same login and password used for the Registration Portal.
Please allow up to 15 minutes after registration for the course to appear on your BlackBoard page.
Registration, cancellation, withdrawal and all other CPA Ontario PD policies can be found here.
Speaker(s)
TDWI is the leading provider of education and research for business intelligence, analytics, and data management professionals. TDWI’s vendor-neutral training is led by experienced practitioners, and has earned a world-wide reputation for being comprehensive, practical, and actionable.
Dean Abbott is co-founder and chief data scientist of Smarter HQ, Inc. He is an internationally recognized data mining and predictive analytics expert and conference speaker with over two decades of experience applying advanced algorithms to real-world problems.
William Henry is a data scientist and owner of Henry Analytics. He works with companies such as RiskPulse, DeVine Consulting, Intently, and the University of California Irvine Extension. Relatively new to the field of data science, William offers a unique perspective to language programming.Dr. Natasha Balac is the founder and president and CEO of Data Insight Discovery, Inc. She has worked extensively in data mining, analytics and bioinformatics in the biotech industry. She has been with the University of California San Diego since 2003, and currently teaches at the CalIT2/Qualcomm Institute.
John Akred is the chief technology officer of Silicon Valley Data Science, and has over 15 years of experience in advanced analytical solutions and analytical system architectures. An expert in the areas of applied business analytics, machine learning, predictive analytics, and operational data mining. John has worked with clients from the US Postal Service to Xcel Energy.