Big Data Analytics with AI
Unlock the Power of Big Data with AI-Driven Analytics
Skills you will gain:
The program focuses on integrating AI algorithms with big data tools to enhance analytics capabilities. Participants will learn to use distributed systems like Hadoop and Spark for processing big data and deploying machine learning models for real-time and batch analytics.
Aim: This program is designed to help professionals and researchers understand how AI-driven techniques are applied to big data for extracting valuable insights. It covers end-to-end data processing, predictive analytics, and AI-enhanced decision-making in industries using large-scale data.
Program Objectives:
- Learn to process big data using distributed systems like Hadoop and Spark.
- Apply AI algorithms to analyze big data for decision-making.
- Implement predictive analytics with AI-driven forecasting models.
- Build real-time AI models for dynamic data environments.
- Visualize big data using AI-enhanced tools and techniques.
What you will learn?
- Introduction to Big Data and AI
- Overview of Big Data and Its Characteristics (Volume, Velocity, Variety)
- Introduction to AI and Machine Learning in Big Data
- Key Big Data Applications in AI (e.g., Healthcare, Finance, IoT)
- Big Data Tools and Frameworks
- Hadoop Ecosystem (HDFS, MapReduce, YARN)
- Apache Spark for Big Data Processing
- Introduction to Cloud Platforms (AWS, Azure, GCP) for Big Data
- Data Storage and Management
- Structured, Semi-Structured, and Unstructured Data
- NoSQL Databases (Cassandra, MongoDB, HBase)
- Data Warehousing and Distributed Storage Systems
- Data Ingestion and ETL Pipelines
- Data Collection and Integration
- Real-time Data Streaming with Kafka and Flume
- Building ETL (Extract, Transform, Load) Pipelines
- AI and Machine Learning on Big Data
- Introduction to Distributed Machine Learning
- Scalable Machine Learning Algorithms on Spark MLlib
- Working with Big Data in Python (PySpark, Dask)
- Deep Learning for Big Data
- Handling Big Data with Neural Networks
- Using TensorFlow and Keras for Large-Scale Deep Learning
- Distributed Deep Learning on Spark and Kubernetes
- Natural Language Processing (NLP) on Big Data
- Text Analytics with Big Data (Processing Large Textual Datasets)
- Large-Scale NLP with BERT, GPT on Big Data Systems
- Applications of NLP in Big Data (e.g., Sentiment Analysis, Topic Modeling)
- Big Data Analytics with AI in Computer Vision
- Handling Large-Scale Image Data
- Distributed CNN Training with Big Data
- Image Classification, Object Detection on Big Data Systems
- Big Data Visualization and Insights
- Visualizing Large Datasets with Tools like Tableau, Power BI
- Big Data Dashboards and Reporting
- Real-Time Data Visualization with AI-driven Insights
- Big Data and AI Ethics
- Ethical Concerns in AI with Big Data
- Data Privacy and Security Issues
- Bias in Big Data Analytics and AI
- Big Data Case Studies and Real-World Applications
- Use Cases in Healthcare, Finance, Retail
- Case Studies on AI Applications (e.g., Fraud Detection, Predictive Maintenance)
- Hands-On Implementation in Real-World Scenarios
Intended For :
Data engineers, data scientists, AI researchers, and big data analysts focused on integrating AI with big data tools.
Career Supporting Skills