Course Description

The AI Data certification provides professionals with cutting-edge skills in Data Science and Artificial Intelligence (AI). Covering key concepts like Data Science Foundations, Statistics, Python Programming, and Data Wrangling, participants gain practical knowledge to excel in a data-driven world. Advanced topics such as Generative AI, Machine Learning, and Predictive Analytics prepare learners for solving complex challenges. This program includes a capstone project on Employee Attrition Prediction, emphasizing Data-Driven Decision-Making and Compelling Data Storytelling for actionable business insights. With personalized mentorship, hands-on projects, and immersive resources, learners are equipped for success in AI and Data Science careers.

Course Objectives

  • Learn to manage, preprocess, and analyze data using statistical methods and exploratory techniques to uncover insights.​
  • Build strong programming skills in Python and R, applying them to foundational and advanced machine learning techniques.
  • Employ advanced AI tools and machine learning algorithms for deriving deeper insights and developing predictive models.
  • Master the art of presenting data effectively and making informed, data-driven business decisions.

Course Agenda

  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

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.