Big Data Science with AI, ML, IOT

Course Overview

The “Big Data Science with AI, ML, IoT, Blockchain & Cloud Computing” course is an advanced, interdisciplinary program designed to prepare learners for the data-driven and intelligent future of technology. This program provides a robust foundation in Big Data Processing, Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Blockchain, and Cloud Computing, covering the tools, platforms, and techniques driving the digital revolution.

Through a mix of theoretical foundations and hands-on practical applications, learners will gain the skills required to build smart, scalable, and secure data-driven systems deployed on cloud-based infrastructures.

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🧠 Course Modules

📊 1. Big Data Science

• Data Processing & Storage
  • Apache Hadoop & Spark
  • NoSQL Databases: MongoDB, Cassandra, Neo4j
  • Scalable SQL Databases: PostgreSQL, MySQL Clustering
• Data Warehousing & ETL
  • Tools: Apache Kafka, NiFi, Talend, Informatica PowerCenter
• Data Visualization
  • Platforms: Tableau, Power BI
  • Python Libraries: Matplotlib, Seaborn, Plotly

🤖 2. Artificial Intelligence (AI) & Machine Learning (ML)

• Languages: Python, R
• ML Frameworks
  • TensorFlow, PyTorch, Keras, Scikit-learn, Transformers (NLP)
• Dev Environments
  • Jupyter Notebook, Google Colab, PyCharm, VS Code
• Cloud AI Platforms
  • Google Vertex AI, Amazon SageMaker, Azure ML

🌐 3. Internet of Things (IoT)

• IoT Platforms
  • AWS IoT Core, Azure IoT Hub, Google Cloud IoT, ThingsBoard
• Device Programming
  • Python (MicroPython), C/C++, Node-RED
• Simulators & Protocols
  • Cisco Packet Tracer, CoAP Tools

🔗 4. Blockchain Technology

• Blockchain Platforms
  • Ethereum, Hyperledger Fabric, Solana, Binance Smart Chain
• Smart Contract Development
  • Languages: Solidity, Go, JavaScript
  • Tools: Truffle, Hardhat, Remix IDE

☁️ 5. Cloud Computing

• Major Cloud Platforms
  • AWS, Microsoft Azure, Google Cloud Platform (GCP)
• Core Cloud Services
  • Compute: EC2, Azure VMs, GCE
  • Storage: S3, Azure Blob, Google Cloud Storage
  • Databases: RDS, Cosmos DB, Firestore, etc.
  • Networking: VPC services
• Containerization & Orchestration
  • Docker, Kubernetes
• Infrastructure as Code (IaC)
  • Terraform, CloudFormation, ARM templates, GCP Deployment Manager
• Serverless Computing
  • AWS Lambda, Azure Functions, Google Cloud Functions

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✅ Why Take This Course?

• End-to-End Skill Set: Learn everything from data ingestion to deploying ML/AI models on cloud platforms.
• Industry-Relevant Tools: Gain hands-on expertise in tools used by leading tech companies.
• Capstone Projects & Case Studies: Apply your learning to real-world challenges.
• Future-Ready Curriculum: Be equipped to tackle next-gen tech like smart cities, intelligent analytics, blockchain applications, and more.

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📌 Who Should Enroll?

• Graduates and working professionals aiming to build a career in Data Science, AI, IoT, or Cloud.
• Software developers, data analysts, network engineers, system architects.
• Entrepreneurs and technology enthusiasts looking to build scalable, intelligent systems.

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🎯 Learning Outcomes

By the end of the course, learners will:

• Understand and implement big data pipelines and real-time analytics.
• Build, train, and deploy machine learning models on cloud platforms.
• Connect, manage, and analyze IoT devices and data.
• Design smart contracts and decentralized applications (dApps).
• Use cloud-native tools to scale and secure modern tech infrastructures.