AI+ Data™

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

Módulos

  • 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

Herramientas de IA

  • Google Colab
  • MLflow
  • Alteryx
  • KNIME
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