IBM Skills Academy

Credit Option
Program Type

Build your tech skills with IBM. You'll be taught by Adelphi University experts -- and become IBM credentialed.

Data Science and Design Thinking Certificate

The Innovation Center, in collaboration with the prestigious IBM Skills Academy, is offering a six-week online class led by Adelphi experts who are IBM Skills Academy-trained. It’s the best of both worlds: you’ll earn a digital badge from one of the world’s top names in tech, and you’ll be taught by an instructor from a U.S. News & World Report Best College.

Understanding data — and how to use it — is a critical part of any career today.  IBM Skills Academy will give you a competitive edge, helping you to make better decisions and optimize any business operation. You’ll engage in role-playing challenge-based scenarios to propose real-world solutions.

If you are interested in applying for an entry-level job in data science-related fields, this course would be an excellent fit.

Earn these digital badges upon completion of this course. You can easily add these to your resume, your Linkedin or other social media accounts.

IBM Data Science Practitioner - Certificate
Enterprise Design Thinking Practitioner
Certificate of Completion

Goals for Your Experience

Real-World Applications

Engage in role-playing challenge-based scenarios to propose real-world solutions.

Cross-Disciplinary Experiences

Explore data science industry case studies: transportation, automotive, human resources, aerospace, banking, and healthcare.

Analytical Skills

Gain a competitive edge using a low-code cloud-based platform for data science -IBM Watson Studio.

Design Thinking

Experience teamwork agile industry practices using Design Thinking.

Technical Expertise

Use popular open-source data science frameworks including Jupyter notebooks and Python.

Team Building

Engage with other students from different backgrounds and learn how to collaborate remotely and add to each other’s expertise to create better solutions.

Program Options & Costs

NOTE: Lectures will not be recorded.  You will be not able to drop this course or submit for a refund once this  IBM Skills Academy course is activated for you.

Status Course Rates Lab Fee
Students $990 $150
Staff $950 $150
Other Individuals $1200 $150

*Corporate discount rates for groups of 7 students or more

Adelphi Faculty interested in taking this program please reach out directly to our team via email:

Timing & Program Format

Summer 2022 course dates: May 26 – June 30

Register Now

This is a online synchronous course, meaning classes will be held at regular times.

Schedule: Monday/Tuesday/Wednesday from 6:00 p.m. – 7:30 p.m. EST

Students should plan for an average weekly commitment of 10-12 hours a week. Each week students will engage in:

  • Active Learning: 4.5 hours of active learning participating in online instructor-led lectures, and design thinking workshops.
  • Self-Paced: 5 hours completing labs, class preparation activities, and office hour visits

Program Format

Concepts (25%)

Expand knowledge and understanding of the topics through lectures, training, examples, videos, and quizzes.

Hands-on Labs (35%)

Implement concepts learned through simulations, hands-on labs, and games.

Group Work Activities (40%)

Understand the real-world impact of topics covered with a deep dive into industry case studies.

Your Course Journey for the IBM Skills Academy Data Science Program

Lecture 1 – Accessing IBM Cloud and Watson Studio Guide

  • Learn the broad definition of Data Science
  • Explore the history and evolution of data science
  • Understand the factors contributing to the growth of data
  • Explore the domains involved in the field of data science
  • Understand the critical roles involved in data science projects

Lab Challenge 1 – Data Science Landscape

Lecture 2 – Data Science Methodology

  • Understand data analytics lifecycle
  • Explore a data analytics use case: Chicago bike-share company
  • Explore the different methodologies for Data Analysis
  • Explore the Data Science method and the roles involved

Lab Challenge 2 – Explore and Understand Data Guide

Lecture 3 – Data Science on the Cloud

  • Understand the need for an integrated environment for Data Science Projects.
  • Explore the benefits of Data Science integrated environments hosted on the cloud.
  • Understand concepts such as object storage, data refinery, machine learning, visual recognition, and model building.
  • Evaluate the relationship between popular data science and open source frameworks.

Lecture 4 – Explore and Prepare Data

  • Explore the business understanding phase
  • Understand the data exploration activity
  • Understand the data preparation activity
  • Visualize the process of data wrangling in action using popular tools

Lecture 5 – Represent and Transform Data

  • Understand statistics and representation techniques that draw from descriptive statistics.
  • Outline the data transformation activities that consider multivariate data points.
  • Reveal how to Represent and Transform unstructured data using 1-hot encoding.
  • Explore data manipulation technologies and the open-source tools used in data representation and transformation.

Lecture 6 – Data Visualization

  • Verify how Decision-centered Visualization begins with understanding the purpose, audience, data, and context of a human-centered reflection.
  • Explore the fundamentals of Visualization and avoid “tricky” situations.
  • Understand common graphs and how they may best tell the stories from different perspectives.
  • Outline common tools used in data visualization.

Lecture 7 – Data Modeling

  • Outline modeling techniques including the use of training and test data sets.
  • Understand machine learning techniques that span predictions made by brute statistics versus neutral networks.
  • Elaborate on the distinction of accuracy, precision, and recall while illustrating how you may need one over the other.
  • Understand various model deployment techniques.

Lecture 8 – Machine Learning Algorithms 

  • Understand the various approaches to Machine Learning including where and when it is used
  • Elaborate the differences between Regression and Neural Nets for prediction results
  • Illustrate a Decision Tree Classifier and predict from a sample use-case
  • Understand machine learning framework and platforms most commonly used by data scientists

Design Thinking Methodology Introduction
This week we will break down the design thinking process and workshop journey.

  • Empathy Map
  • Pain Points
  • Intent
  • Big Idea
  • Data
  • Understand
  • Reasoning
  • Knowledge
  • Playbacks

Design Thinking Methodology Team Exercise 
This week the students will be divided into two teams to complete a design thinking brainstorming session.

Workshop Recap and Exam Prep 
This week we will go through practice exams, study guides, and Q&A’s to cover any questions and concerns to prepare for the exit exam.

Exam Prep and Final Examination
Students will take the final exam from the IBM Dashboard to receive their IBM Data Science Certificate.

More Info
Swirbul Library First Floor
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