• Internet of Things – history and evolution
• IoT use-cases
• Economic potentials
• Future trends

• IoT Network and Device
• Platform and Application Architecture
• Open source initiatives
• Industry 4.0 – Reference Architecture
• Reference Architectural Model of Industry 4.0 – IIRC, Industrial Internet Consortium (IIC), Industrial Internet Reference Architecture (IIRA)

• Understanding Data, Information, Knowledge and Wisdom (DIKW Pyramid)
• Types of data
• Physical and logical representation of data
• Natural languages – Symbolic representation
• Computer languages – Data encoding, storage and interpretation
• Structured and unstructured data

• IoT Devices – Sensor and control nodes
• Data collection & processing – Edge & Cloud
• Web services architecture and protocols – HTTP & MQTT

• Understanding IoT enterprise architecture
• Data aggregation, processing and analytics at the edge
• Addressing IT and OT integration
• IoT brokers
• AWS Greengrass and Azure IoT edge solutions

• Selection of sensor to capture right set of data
• Handling of sensor data
• Analog to digital conversion
• Event detection
• Data pre-processing
• Integration of different data sources
• Heterogeneity and distributed nature
• Limitations of Sensor Nodes
• Real-Time/Streaming Analytics , Descriptive, Diagnostic, Predictive and Prescriptive
• Analytics/Machine Learning using Python advance packages: NumPy, SciPy, Matplotlib, Pandas and Sci-kit learn

• Python: History and background
• Python IDEs
• Anaconda Python distribution

• Introduction
• Setup and getting started

• Data handling in Python
• Dynamic typing feature of Python
• Sequences and data structures – Strings, lists, tuples, dictionary and sets

• Arithmetic assignment
• Comparison
• Logical (or Relational) operators
• Conditional (or ternary) operators

• If , If-elif structures
• While and For loops
• The range() Function
• Break and Continue Statements, and Else clauses on Loops
• Pass statement

• Local variables
• Default argument values and Returning values
• Keyword & Positional arguments
• Arbitrary argument lists
• Documentation strings
• Unpacking argument lists

• Lambda functions
• List comprehension
• Map, apply, reduce & filter

• Opening a File
• Reading from a file
• Writing to a file
• Closing a File
• File handling using With statement
• Reading directories & other basic directory operations (getcwd, mkdir, chdir etc.)
• Renaming & deleting files

• Building modules
• Executing modules as scripts, The Module Search Path
• ‘Compiled’ Python files
• Standard Modules
• The dir() Function
• Packages

• OOPs fundamentals
• Class definition syntax, Class objects, Instance objects, Method objects; Instantiation
• Data Member – Class variable/Instance variable
• Function and Operator overloading
• Inheritance

• Handling Exceptions
• Try-except, Else clause and Finally clause
• Raising Exceptions
• User-defined Exceptions

NumPy

• One-dimensional arrays, Multi-dimensional arrays
• NumPy arrays compared to Python lists
• Modifying parts of an array

Pandas 

• Series and DataFrames
• Accessing elements from a series
• Series alignment
• Element-wise operations
• Creating a DataFrame from NumPy Array, Series CSV files
• Getting columns and rows
• Data wrangling

IoT data – Descriptive analytics using Pandas 

Plotting with Matplotlib and Seaborn

• What is Machine Learning?
• Introduction to Machine Learning
• Types of Machine Learning
• Basics of statistics and linear algebra
• Supervised machine learning – Regression, Classification
• Unsupervised learning – Clustering
• Dimensionality reduction
• Model performance evaluation
• Time series analysis – IoT data
• Predictive maintenance IoT system application and case study

Public, Private and Hybrid cloud platforms and deployment strategy

IaaS, SaaS, PaaS models

Cloud components and services

• Device connectivity & management
• Cloud brokers
• Rules Engines
• Databases
• Visualization
• Reporting
• Notification/Alarm management

Example platforms: AWS IoT, Microsoft Azure

• Overview of security and privacy in Information System
• Principles of IoT security
• IoT security guidance
• Identify the known threats, risks, vulnerabilities and privacy issues
• Security architectures