Data Science Practitioner
IBM Skills Academy
The IBM Skills Academy Program is IBM’s premier training and digital badging worldwide program with curriculum aligned to high-demand jobs in the new digital-age technology job market. The Data Science program covers several open source technologies including the premier IBM Watson Studio platform.
Course modules include:
- Data Science Methodology
- Data Science on the Cloud
- Data Cleansing
- Data Modeling
- Data Visualization
- IBM Enterprise Design Thinking
Upon successful completion of this course and exam, participants are eligible for the IBM Data Science Practitioner digital badge. Additional credentials may be earned, including IBM Watson Studio Essentials and IBM Design Thinking Practitioner digital badges.
Prerequisites: Introduction to R Programming for Data Science and Machine Learning or equivalent experience, strong MS Excel skills. Knowledge of statistics and / or math background helpful (but not necessary).
Days: Tuesday and Thursday evenings
Dates: September 21 through December 16, 2021 (skip 11/25, 11/30 & 12/2)
Times: 6:00 pm – 9:00 pm
And: Three Saturdays, October 2-23, 1:00-4:00 pm
Cost: $2,450
Location: Remote with live instructor
Course Information: COMP 2205 #83846
Course Contact Hours: 80 Total
Funding may be available for this program. Contact Kristine.Bunyea@sunywcc.edu for eligibility.
To register please call 914-606-6830, press 1. Thank you.
Course Outcomes:
Upon completion of this course, the participant will have:
- Acquired skills and understanding of foundational Data Science concepts and technologies
- Demonstrated proficiency and understanding of Data Science technical topics and design thinking
- Gained the ability to apply the concepts and technology of Data Science with the applicable open source tools that are relevant to real-world scenarios
Course Outline:
Session 1: Lecture 1 – Data Science Landscape Lecture
Session 2: Lecture 1 – The Future of Cognitive Computing Lab 1 – Accessing IBM Cloud
Session 3: Lecture 2 – Data Science Methodology Presentation Intro to Watson Studio Walkthrough
Session 4: Lecture 3 – Data Science on the Cloud Lab 2 – Exploring and Preparing Automotive Data
Session 5: Introduction to R Using R Studio
Session 6: Introduction to R Using R Studio
Session 7: Introduction to R Using R Studio Lecture 4 – Explore and Prepare Data
Session 8: Intro to Statistics Using Excel Stock Market Predictor Review (Python/Watson Studio)
Session 9: Intro to Python (Anaconda)
Session 10: Intro to Python (Anaconda)
Session 11: Intro to Python (Anaconda)
Session 12: Lecture 5 – Represent and Transform Data, Heart Disease – Classifications (Python/Anaconda)
Session 13: Design Thinking Lecture, Design Thinking Workshop for Data Science
Session 14: Lab 3 – Validating Automotive Data Guide (Watson Studio)
Session 15: Lecture 6 – Data Visualization and Presentation, K-Means Clustering Lecture/Exercise (Python Anaconda)
Session 16: K-Means Clustering Lecture/Exercise (Python Anaconda)
Session 17: Lab 4 – Data Refinery Visualization Guide, Implement Weather Predictor Model (Watson Studio)
Session 18: Lab 5 – Visualizing Automotive Data Guide
Session 19: Lab 6 – Predict Heart Failure
Session 20: Lecture 7 – Data Modeling Presentation, Neural Network Lecture/Exercises
Session 21: Lab 7 – Apply ML Models To Employee Attrition Guide, Houston Flood Data Exercise (Python/IBM Cloud)
Session 22: Lecture 8 – Machine Learning Algorithms
Session 23: Lab 6 – Predict Heart Failure Review, Certification Quiz Review
Session 24: Q-Learning algorithm (IBM Studio Notebook)
Session 25: Q-Learning algorithm (IBM Studio Notebook), Final Project Prep/Certification Quiz Review
Session 26: Final Project Prep/Certification Quiz Review
Session 27: Final Project Prep and Presentations/Certification Quiz Review
Final Exam
Who Will Benefit
You will benefit most from the IBM Data Science Practitioner digital badge if you are a:
- Research Analyst
- Business Analyst
- Data Analyst
- Data Scientist
- Project Manager
- Data Engineer
- BI (Business Intelligence) Analyst
- Software Developer
For further information, please contact Kristine Bunyea at Kristine.Bunyea@sunywcc.edu or 914-606-7904.