AI+ Data™

AT-120

Mastering AI, Maximizing Data: Your Path to Innovation
  • Core Concepts Covered: Data Science foundations, Python, Statistics, and Data Wrangling
  • Advanced Topics: Dive into Generative AI, Machine Learning, and Predictive Analytics
  • Capstone Application: Solve real-world problems like employee attrition with AI
  • Career Readiness: Develop skills for AI-driven data science roles with hands-on mentorship
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Why This Certification Matters

Demand for Certified Experts: Organizations seek certified experts who can transform complex data into actionable insights while ensuring data integrity and privacy.
Mitigating Data and AI Risks: Poor handling of data and AI technologies can lead to inaccurate analysis and business risks. This certification helps professionals mitigate such challenges.
Designing AI-Driven Data Strategies: Certified professionals play a crucial role in designing AI-driven data strategies that optimize performance and align with regulatory standards.
Career Advancement: As AI-powered data solutions become essential for businesses, this certification provides professionals with a competitive edge in advancing their careers.

At a Glance: Course + Exam Overview

Program Name 
AI+ Data™
Included 
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration 
  • Instructor-Led: 5 days (live or virtual) 
  • Self-Paced: 30 hours of content
Prerequisites
Basic knowledge of computer science and statistics, data analysis, fundamental AI/ML concepts, Python and R.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience
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Who Should Enroll?

  • Data Analysts & Scientists: Enhance data analysis capabilities using AI for predictive modeling and decision-making. 

  • Business Intelligence Professionals: Leverage AI to uncover insights, trends, and opportunities in complex data sets. 

  • IT Specialists & System Integrators: Implement AI-powered solutions to optimize data management and infrastructure. 

  • Data Engineers: Design and develop AI-driven data pipelines and architectures for scalable solutions. 

  • Students & New Graduates: Build valuable AI and data science skills to thrive in an increasingly data-driven world. 

Job Roles & Industry Outlook 

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AI Data Scientist

Analyzes complex data to extract insights, builds predictive models, employs statistical methods, and communicates findings to influence decision-making.

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AI Machine Learning Engineer

Designs and develops machine learning systems, implements algorithms, optimizes data pipelines, and integrates models into scalable, production-ready applications.

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AI Engineer

Develops artificial intelligence solutions, programs neural networks, optimizes AI algorithms, ensures ethical AI deployment, and troubleshoots AI systems.

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AI Data Analyst

Interprets data, generates reports, identifies trends, supports business decisions with actionable insights, and utilizes visualization tools to present data.

Industry Growth: Fueling Data-Driven Decision Making Across All Industries

  • The global AI data science market is projected to expand at a CAGR of 37.4% from 2023 to 2030. (Source: Grand View Research)
  • AI-powered data analytics is transforming industries such as finance, marketing, and retail, driving innovation in data processing and decision-making.
  • The adoption of AI-enhanced data solutions is accelerating, with organizations utilizing AI for real-time data analysis, predictive insights.
  • AI-driven automation is becoming critical for data-intensive industries, streamlining processes and improving operational efficiency across sectors.
  • AI in data science is revolutionizing industries like e-commerce, supply chain management, and customer service by enhancing data-driven decision-making.
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Skills You’ll Gain

  • Data Visualization Techniques
  • Data Quality and Bias Mitigation
  • Deep Learning for Data Processing
  • Statistical Modeling
  • Big Data Technologies

What You'll Learn

  1. Course Introduction
  1. 1.1 Introduction to Data Science
  2. 1.2 Data Science Life Cycle
  3. 1.3 Applications of Data Science
  1. 2.1 Basic Concepts of Statistics
  2. 2.2 Probability Theory
  3. 2.3 Statistical Inference
  1. 3.1 Types of Data
  2. 3.2 Data Sources
  3. 3.3 Data Storage Technologies
  1. 4.1 Introduction to Python for Data Science
  2. 4.2 Introduction to R for Data Science
  1. 5.1 Data Imputation Techniques
  2. 5.2 Handling Outliers and Data Transformation
  1. 6.1 Introduction to EDA
  2. 6.2 Data Visualization
  1. 7.1 Introduction to Generative AI Tools
  2. 7.2 Applications of Generative AI
  1. 8.1 Introduction to Supervised Learning Algorithms
  2. 8.2 Introduction to Unsupervised Learning
  3. 8.3 Different Algorithms for Clustering
  4. 8.4 Association Rule Learning with Implementation
  1. 9.1 Ensemble Learning Techniques
  2. 9.2 Dimensionality Reduction
  3. 9.3 Advanced Optimization Techniques
  1. 10.1 Introduction to Data-Driven Decision Making
  2. 10.2 Open Source Tools for Data-Driven Decision Making
  3. 10.3 Deriving Data-Driven Insights from Sales Dataset
  1. 11.1 Understanding the Power of Data Storytelling
  2. 11.2 Identifying Use Cases and Business Relevance
  3. 11.3 Crafting Compelling Narratives
  4. 11.4 Visualizing Data for Impact
  1. 12.1 Project Introduction and Problem Statement
  2. 12.2 Data Collection and Preparation
  3. 12.3 Data Analysis and Modeling
  4. 12.4 Data Storytelling and Presentation

Tools You’ll Master

Tool Google Colab

Google Colab

Tool MLflow

MLflow

Tool Alteryx

Alteryx

Tool KNIME

KNIME

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.

Exam Details

Duration

90 minutes

Passing Score

70% (35/50)

Format

50 multiple-choice/multiple-response questions

Delivery Method

Online via proctored exam platform (flexible scheduling)

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%

Choose the Format That Fits Your Schedule

What’s Included (One-Year Subscription + All Updates):

  • 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

Instructor-Led (Live Virtual/Classroom)

  • 5 days of intensive training with live demos
  • Real-time Q&A, peer collaboration, and hands-on labs
  • Led by AI Certified Trainers and delivered through Authorized Training Partners
Purchase Instructor-Led Course

Self-Paced Online

  • ~30 hours of on-demand video lessons, e-book, podcasts, and interactive labs
  • Learn anywhere, anytime, with modular quizzes to track progress
Purchase Self-Paced Course

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Frequently Asked Questions

The certification covers Data Science Foundations, Statistics, Programming, and Data Wrangling, along with advanced subjects such as Generative AI and Machine Learning.

The certification provides participants with the necessary tools and skills to handle complex data challenges, such as cleaning, transforming, and analyzing data.

Graduates of the AI+ Data™ certification program can pursue roles such as Data Scientist, Machine Learning Engineer, Data Analyst, AI Consultant, and other data-driven positions.

Participants will gain skills in data analysis, machine learning, data visualization, data wrangling, and predictive analytics, along with proficiency in Python and R.

Yes, the AI+ Data™ certification is designed to be flexible and can be pursued while working full-time. The course materials are available online.

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