Cambridge
Academy
In London

Introduction

AI provides powerful tools to analyze large, complex, and unstructured data sets. This course prepares analysts to handle big data challenges with AI algorithms.

Objectives

- Understand AI’s role in big data analysis.

- Apply AI for structured and unstructured data.

- Use AI for real-time big data processing.

- Explore AI cloud platforms for big data analytics.

Audience

- Big data engineers

- Data analysts

- IT architects

- Data scientists

5-Day Outline

Day 1: AI & Big Data Overview

- AI in big data ecosystems

- Challenges in big data analysis

- Tools: Hadoop + AI, Spark MLlib, AWS AI Services

- Case study: AI in financial big data

- Discussion: AI vs. traditional big data

Day 2: AI for Structured & Unstructured Data

- AI for structured transactional data

- AI for text analytics (NLP)

- AI for image & video analysis

- Workshop: Unstructured data processing with AI

- Peer feedback session

Day 3: Real-Time Big Data Analytics with AI

- AI for stream data analytics

- Predictive AI in real-time monitoring

- Tools: Apache Kafka, Spark Streaming, Azure AI

- Case study: AI in IoT analytics

- Exercise: Real-time AI pipeline simulation

Day 4: AI Cloud Platforms for Big Data

- AWS, Azure, and Google Cloud AI platforms

- AI for big data pipelines

- Group project: AI big data solution design

- Peer collaboration

- Review session

Day 5: Future of AI in Big Data Analytics

- AI for deep learning on big data

- AI ethics and compliance in big data

- Group presentations: Big data AI projects

- Expert feedback

- Wrap-up & certification