Prerequisites
- Basic Understanding of Computer Science: Familiarity with programming and statistics (beneficial but not mandatory).
- Interest in Data Analytics: A keen passion for analyzing data trends and solving real-world problems.
- Willingness to Learn Python and R: Basic programming skills help, but the program is designed to support beginners.
Exam Details
- Modules (12)
- Examination (1)
- 50 MCQs, 90 Minutes
- Passing Score (70% (35/50))
Exam Blueprint
| Modules | Percentage |
|---|---|
| Foundations of Data Science | 5 |
| Foundations of Statistics | 5 |
| Data Sources and Types | 6 |
| Programming Skills for Data Science | 10 |
| Data Wrangling and Preprocessing | 10 |
| Exploratory Data Analysis | 12 |
| Generative AI Tools for Deriving Insights | 6 |
| Machine Learning | 10 |
| Advance Machine Learning | 10 |
| Data-Driven Decision-Making | 10 |
| Data Storytelling | 6 |
| Capstone Project – Employee Attrition Prediction | 10 |
What you will get
High-Quality Videos, E-book (PDF & Audio), and Podcasts
AI Mentor for Personalized Guidance
Quizzes, Assessments, and Course Resources
Online Proctored Exam with One Free Retake
Comprehensive Exam Study Guide
Why This Certification Matters
Demand for Certified Experts
Organizations are actively seeking certified professionals who can turn complex data into meaningful insights while upholding standards for data integrity and privacy.
Mitigating Data and AI Risks
Improper use of data and AI technologies can lead to flawed analysis and costly business risks. This certification equips professionals to manage these challenges effectively and responsibly.
Designing AI-Driven Data Strategies
Certified individuals play a key role in building AI-powered data strategies that enhance business performance, support innovation, and ensure regulatory compliance.
Career Advancement
As AI-powered data systems become foundational to business success, this certification provides a distinct competitive advantage for professionals seeking to grow in data science and analytics roles.
Who Should Enroll
Data Analysts and Data Scientists
Enhance your data analysis capabilities with AI-driven techniques for predictive modeling and smarter decision-making.
Business Intelligence Professionals
Leverage AI to extract deeper insights, identify trends, and uncover strategic opportunities within large data sets.
IT Specialists and System Integrators
Implement AI-powered solutions to streamline data infrastructure, improve system performance, and support enterprise scalability.
Data Engineers
Design and build robust, AI-driven data pipelines and architectures that support real-time analytics and machine learning applications.
Students and New Graduates
Gain essential skills in AI and data science to prepare for careers in today’s fast-evolving, data-driven landscape.
Tools for AI and Data Science
Google Colab
MLflow
Alteryx
KNIME
Prerequisites
Basic understanding of computer science and statistics is helpful but not required
Strong interest in data analysis and working with data-driven insights
Willingness to learn programming languages such as Python and R
Exam Blueprint
- Foundations of Data Science – 5%
- Foundations of Statistics – 5%
- Data Sources and Types – 6%
- Programming Skills for Data Science – 10%
- Data Wrangling and Preprocessing – 10%
- Exploratory Data Analysis – 12%
- Generative AI Tools for Deriving Insights – 6%
- Machine Learning – 10%
- Advance Machine Learning – 10%
- Data-Driven Decision-Making – 10%
- Data Storytelling – 6%
- Capstone Project - Employee Attrition Prediction – 10%
Frequently Asked Questions
What are the key components of the AI+ Data™ certification
The program includes core topics such as data science foundations, Python and R programming, statistics, and data wrangling. It also covers advanced areas like generative AI, machine learning, predictive analytics, and culminates with a hands-on capstone project.
How does this certification prepare participants for data challenges
Participants gain practical experience solving real-world data problems. The course builds proficiency in data cleaning, analysis, visualization, and predictive modeling, empowering learners to tackle challenges across diverse industries.
What are the career opportunities after completing this certification
Graduates can pursue roles such as Data Scientist, Machine Learning Engineer, Data Analyst, AI Consultant, and Business Intelligence Specialist—roles that are in high demand across tech, finance, healthcare, and more.
What skills will I gain from this certification
You will develop expertise in Python and R, data preprocessing, statistical analysis, machine learning, generative AI, data visualization, and storytelling with data. These skills are essential for driving data-informed decisions in modern organizations.
Can I pursue this course while working full-time
Yes. The certification is designed with flexibility in mind, allowing professionals to learn at their own pace while managing work commitments. Course materials are accessible online and structured for both live and self-paced learning.
