sas logo
Young business colleagues studying data around a laptop in office

Machine Learning 101

Are you ready to dive deep into the world of analytics and machine learning? 

Whether you're looking to enhance your career or start a new journey in data science, our upcoming SAS courses are tailored just for you

Inquire now MACHINE Learning 101

Featured Courses:

  1. The Modeling Life Cycle for Data Scientists

    Date: April 10, 2025
    Mode: In-Person Class
    Time: 9 AM - 5 PM

    This course gives an overview of the statistical methods used by data scientists, with an emphasis on the applicability to business problems. Attendees do not need access to software for this course, and the mathematical details are kept to a minimum.

  2. Statistics You Need to Know for Machine Learning

    Date: April 24-25, 2025
    Mode: In-Person Class
    Time: 9 AM - 5 PM

    Transition from traditional statistical modeling to the machine learning world! This course introduces the statistical background necessary for machine learning and prepares you to become a data scientist. It lays the groundwork for future instruction on machine learning, including its underlying statistical methodologies, and helps you develop a deeper understanding of machine learning models.

Venue:

SAS Institute (Philippines), Inc.
▪ 9/F Asian Century Center, 27th Street corner of 3rd and 4th Avenues, Bonifacio Global City, Taguig, Philippines.

About the expert


Dr. Jeffry Tejada
Professor
University of Philipines

Dr. Jeffry Tejada is an Associate Professor of Statistics at the University of the Philippines, where he teaches courses on both theoretical and applied statistics. Some of these courses include probability and inference, data analytics, machine learning, statistical software, just to name a few. He also has more than 20 years of experience in providing consulting and training expertise in analytics and machine learning for various organizations. His work spans multiple industries, such as software development, telecommunications, banking, manufacturing, and retail. Recent engagements include credit risk modeling, data management, propensity scoring, and time series forecasting.

Have a SAS profile? To complete this form automatically Sign In

*
*
*
*
 
*
*
*
*
*
 The Modeling Life Cycle for Data Scientists
 Statistics You Need to Know for Machine Learning
 Machine Learning Roadmap

All personal information will be handled in accordance with the SAS Privacy Statement.

 
  Yes, I would like to receive occasional emails from SAS Institute Inc. and its affiliates about SAS products and services. I understand that I can withdraw my consent at any time by clicking the opt-out link in the emails.
 
 

Machine Learning Roadmap

Intermediate

  • SAS® Visual Statistics in SAS® Viya®: Interactive Model Building
  • Interactive Machine Learning in SAS® Viya®
  • Machine Learning Using SAS® Viya®

Advanced

  • Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls
  • The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats
  • Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership

Earn SAS Verified Digital Badges

Digital badges can be used in email signatures or digital résumés, and on social media sites such as LinkedIn, Facebook and Twitter. This digital image contains verified metadata that describes your qualifications and the process required to earn them.

  • Web-enabled version of your credential that can be shared online
  • Labor market insights that connect your skills to jobs
  • Trusted method for real-time credential verification.

Why Attain:

  • Machine learning automates the analytical model building process, allowing systems to learn from data, identify patterns, and make decisions with minimal human intervention.
  • Predictive analytics leverages data, statistical algorithms, and machine learning techniques to forecast future outcomes based on historical data.
  • With SAS, predictive analytics is accessible beyond just mathematicians and statisticians.
  • Business analysts and experts across various sectors—banking, retail, healthcare, manufacturing, and more.
  • Harness these technologies to detect fraud, optimize marketing campaigns, improve operations, and reduce risk.

We’re excited to support your journey in data science. Join us to gain valuable insights, practical skills, and a digital Badge that showcases your expertise.

Secure your spot today and step into the future of data science with SAS.