Home Courses Corporate Training Book Training Training Calendar AI+ ALL ACCESS Testimonials About Contact
About Contact

AI+ Dataā„¢ ā€“ Instructor-Led Programme Delivery

Ā 

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.

Ā 

Skills Youā€™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
  1. 1. Understanding AI Agents
  2. 2. Case Studies
  3. 3. Hands-On Practice with AI Agents