AI+ Data

The AI+ Data certification equips professionals with vital skills for data science. It covers key concepts like Data Science Foundations, Statistics, Programming, and Data Wrangling. Participants delve into advanced topics such as Generative AI and Machine Learning, preparing them for complex data challenges. The program includes a hands-on capstone project focusing on Employee Attrition Prediction. Emphasis is placed on Data-Driven Decision-Making and Data Storytelling for actionable insights. Personalized mentorship, immersive projects, and cutting-edge resources ensure a transformative learning journey, preparing individuals for success in AI and data science.

Upon successful completion of the AI+ Data certification, students will acquire a comprehensive grasp of foundational data science principles and methodologies. They will proficiently analyze, model, and extract insights from intricate datasets. Through hands-on practice in Python and R, participants will master data manipulation, visualization, and modeling techniques. They'll explore diverse data sources and storage technologies, honing skills in data wrangling and exploratory analysis for informed decision-making. By delving into advanced topics like generative AI and ensemble learning, students will tackle complex data challenges. Furthermore, they'll refine communication skills, effectively conveying data insights through storytelling and visualization. Real-world projects, including an employee attrition prediction capstone, will showcase their ability to derive actionable solutions from data.

Prerequisites

• Basic knowledge of computer science and statistics (beneficial but not mandatory)

• Keen interest in data analysis

• Willingness to learn programming languages such as Python and R

Exams

• Number of Questions: 50

• Passing Score: 35/50 or 70%

• Duration: 90 Minutes

• Format: Online via AI Proctoring platform

• Question Type: Multiple Choice/Multiple Response

Exam Overview:

• 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%