AI+ Data Practitioner™ eLearning

Formerly known as 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

Duur: 5 dag(en)

  • 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.

  • 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.

Inhoud

Course Overview
Module 1: Foundations of Data Science
  • 1.1 Introduction to Data Science
  • 1.2 Data Science Life Cycle
  • 1.3 Applications of Data Science
Module 2: Foundations of Statistics
  • 2.1 Basic Concepts of Statistics
  • 2.2 Probability Theory
  • 2.3 Statistical Inference
Module 3: Data Sources and Types
  • 3.1 Types of Data
  • 3.2 Data Sources
  • 3.3 Data Storage Technologies
Module 4: Programming Skills for Data Science
  • 4.1 Introduction to Python for Data Science
  • 4.2 Introduction to R for Data Science
Module 5: Data Wrangling and Preprocessing
  • 5.1 Data Imputation Techniques
  • 5.2 Handling Outliers and Data Transformation
Module 6: Exploratory Data Analysis (EDA)
  • 6.1 Introduction to EDA
  • 6.2 Data Visualization
Module 7: Generative AI Tools for Deriving Insights
  • 7.1 Introduction to Generative AI Tools
  • 7.2 Applications of Generative AI
Module 8: Machine Learning
  • 8.1 Introduction to Supervised Learning Algorithms
  • 8.2 Introduction to Unsupervised Learning
  • 8.3 Different Algorithms for Clustering
  • 8.4 Association Rule Learning with Implementation
Module 9: Advance Machine Learning
  • 9.1 Ensemble Learning Techniques
  • 9.2 Dimensionality Reduction
  • 9.3 Advanced Optimization Techniques
Module 10: Data-Driven Decision-Making
  • 10.1 Introduction to Data-Driven Decision Making
  • 10.2 Open Source Tools for Data-Driven Decision Making
  • 10.3 Deriving Data-Driven Insights from Sales Dataset
Module 11: Data Storytelling
  • 11.1 Understanding the Power of Data Storytelling
  • 11.2 Identifying Use Cases and Business Relevance
  • 11.3 Crafting Compelling Narratives
  • 11.4 Visualizing Data for Impact
Module 12: Capstone Project – Employee Attrition Prediction
  • 12.1 Project Introduction and Problem Statement
  • 12.2 Data Collection and Preparation
  • 12.3 Data Analysis and Modeling
  • 12.4 Data Storytelling and Presentation
Optional Module: AI Agents for Data Analysis
  • 1. Understanding AI Agents
  • 2. Case Studies
  • 3. Hands-On Practice with AI Agents
Tools you will explore
  • Google Colab
  • MLflow
  • Alteryx
  • KNIME

Lesmethode

Instructor-led OR Self-paced course + Official exam + Digital badge

Kenmerken

Online proctored exam included, with one free retake.
Exam format:

50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.

Voorkennis

  • Basic knowledge of computer science and statistics, data analysis, fundamental AI/ML concepts, Python and R.

AI+ Data Practitioner™ eLearning

€ 510,00 excl. BTW

Artikelnummer: AT-120-E Categorie: Tags: , , ,