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    • AI+ Data™

    • 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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    AI+ Data™
    Price: USD $450.00

    At a Glance: Course + Exam Overview

    Category AI Data & Robotics
    AI Technical
    Program Name AI+ Data™
    Duration
    • Instructor-Led: 5 Days
    • Self-Paced: 40 hours of content
    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 Format 50 questions, 70% passing, 90 Minutes

    What You'll Learn

    • Advanced Data Analysis Techniques
      Learners will acquire skills in managing, preprocessing, and analyzing data using statistical methods and exploratory techniques to uncover insights and patterns.
    • Programming and Machine Learning Proficiency
      Students will develop strong programming skills necessary for data science, along with foundational and advanced machine learning techniques to build predictive models.
    • Application of Generative AI and Machine Learning
      Learners will learn to employ generative AI tools and machine learning algorithms to derive deeper insights from data, enhancing their analytical capabilities.
    • Data-Driven Decision Making and Storytelling
      Students who goes through this course will get the ability to make informed decisions based on data analysis and effectively communicate findings through compelling data storytelling.

    Certification Modules

    Course Overview

    1. Course Introduction Preview

    Module 1: Foundations of Data Science

    1. 1.1 Introduction to Data Science
    2. 1.2 Data Science Life Cycle
    3. 1.3 Applications of Data Science

    Module 2: Foundations of Statistics

    1. 2.1 Basic Concepts of Statistics
    2. 2.2 Probability Theory
    3. 2.3 Statistical Inference

    Module 3: Data Sources and Types

    1. 3.1 Types of Data
    2. 3.2 Data Sources
    3. 3.3 Data Storage Technologies

    Module 4: Programming Skills for Data Science

    1. 4.1 Introduction to Python for Data Science
    2. 4.2 Introduction to R for Data Science

    Module 5: Data Wrangling and Preprocessing

    1. 5.1 Data Imputation Techniques
    2. 5.2 Handling Outliers and Data Transformation

    Module 6: Exploratory Data Analysis (EDA)

    1. 6.1 Introduction to EDA
    2. 6.2 Data Visualization

    Module 7: Generative AI Tools for Deriving Insights

    1. 7.1 Introduction to Generative AI Tools
    2. 7.2 Applications of Generative AI

    Module 8: Machine Learning

    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

    Module 9: Advance Machine Learning

    1. 9.1 Ensemble Learning Techniques
    2. 9.2 Dimensionality Reduction
    3. 9.3 Advanced Optimization Techniques

    Module 10: Data-Driven Decision-Making

    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

    Module 11: Data Storytelling

    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

    Module 12: Capstone Project - Employee Attrition Prediction

    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

    Optional Module: AI Agents for Data Analysis

    1. 1. Understanding AI Agents
    2. 2. Case Studies
    3. 3. Hands-On Practice with AI Agents

    Finish the course and get certified

    Certificate 1

    Industry Opportunities

    • AI Data Scientist
      AI Data Scientist
      Analyzes complex data to extract insights, builds predictive models, employs statistical methods, and communicates findings to influence decision-making.
    • AI Machine Learning Engineer
      AI Machine Learning Engineer
      Designs and develops machine learning systems, implements algorithms, optimizes data pipelines, and integrates models into scalable, production-ready applications.
    • AI Engineer
      AI Engineer
      Develops artificial intelligence solutions, programs neural networks, optimizes AI algorithms, ensures ethical AI deployment, and troubleshoots AI systems.
    • AI Data Analyst
      AI Data Analyst
      Interprets data, generates reports, identifies trends, supports business decisions with actionable insights, and utilizes visualization tools to present data.

    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.

    Prerequisites

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    Exam Details

    Duration

    90 Minutes

    Passing Score

    70%

    Format

    50 multiple-choice/multiple-response questions

    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%
    Course Price: USD $450.00
    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
    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