Programs

Visual Programming for
Non-Programmers

This course is targeted to professional individuals or students of data science who have grasped the Basic understanding of Data Science, Data Processing and Predictive Analytics under KNIME system.

Three main modules ranging from basic undertaking of the KNIME system usage to Deep Learning utilizing Predictive Maintenance Framework that is beneficial for the manufacturing and factory modus operandi. .

Data Science for Non-Programmers with Visual Programming

  • Fundamental of Data Science
  • Visual Programming with KNIME
  • Exploratory Data Analysis
  • Machine Learning

Predictive Maintenance with Time Series

  • Introduction to Time-Series
  • Autoregressive Model
  • Anomalies Detection
  • Predictive Maintenance

Deep Learning with Visual Programming

  • Theory of Deep Learning
  • Neural Network Algorithm
  • Autoencoder Application
  • Recurrent Neural Network

Artificial intelligence & IoT [ AIOT ]

IOT (Internet of Things) can play an important role in optimizing the OEE (Overall Equipment Efficiency), of a production line or even of a complete production plant.

AIOT is transformational and mutually beneficial for both types of technology as AI adds value to IOT through machine learning capabilities and IOT adds value to AI through connectivity, signaling and data exchange.

As IOT networks spread throughout major industries, there will be an increasingly large amount of human-oriented and machine-generated unstructured data. AIOT can provide support for data analytics solutions that can create value out of this IOT-generated data.

IIoT fundamentals

  • Basic knowledge about Dat Science & KNIME The different methods of using KNIME program Data input and output using KNIME

Real-Time operating systems (RTOS) Programming

  • History & types of Metaverse
  • Potentials of Metaverse to Businesses
  • Experiencing Metaverse

AIOT

  • Concept of NFT
  • The platforms and trends
  • Onboarding to NFT

ROS

  • History & types of Metaverse
  • Potentials of Metaverse to Businesses
  • Experiencing Metaverse

Blockchain technology, digital assets & metaverse

The internet is always changing and revolutionizing.

Blockchain technology, NFTs, and the Metaverse are all advancing rapidly. People are eagerly anticipating a speedier and, most importantly, safer version of the internet.

Our programs equip our participants with the necessary skills required to unleash new potentials in the digital space.

Block Chain & Application

  • Concept of Blockchain
  • The use cases
  • Basic to Smart Contract

Metaverse and Its use case

  • History & types of Metaverse
  • Potentials of Metaverse to Businesses
  • Experiencing Metaverse

Non fungible Tokens (NFT)

  • Concept of NFT
  • The platforms and trends
  • Onboarding to NFT

Creating a Good blockchain project

  • Idea Generation
  • Basic Business planning
  • Creating a Road Map

Drone Programs

Dynamic Remotely Operated Navigation Equipment (DRONE) training programs are tailored to specific needs of trainees. Industry-specific advanced drone training in areas such as aerial mapping, asset inspection, smart farming, and smart construction, are provided.

Skills to be equipped include standard operating procedures development, pilot assessment, program management and technological consultation. These skills assist in safely implementing drone projects.

Certified Drone Maintenance & Repair Proficient (CDMRP)

  • Technical analysis and inspection of drone components
  • Service provider proficiency

Certified Drone Operation Program (CDOP)

  • Competency approval and validation of trained pilots
  • Effective transfer of skill and knowledge to learners

Certified Drone Operation Agriculture Proficient (CDOAP)

  • Aerial surveying
  • Plant health indexing
  • Pesticide spraying
  • Improve variable-rate prescription and yield estimation

Remote Pilot Certificate of Competency-Basic (RCoC-B)

  • Authorisation to undertake VLOS (Visual Line of Sight) operations
  • Execute Predefined Risk Assessment (PDRA).

Fostering Creativity in the Fourth Industrial Revolution

Fostering learners with creativity using STEM prototyping activities promotes inventiveness and gives them opportunities to see the connection between the content they have studied and the application of that content in a real-world thru an authentic, creative and fun ways allowing them to imagine, discover and innovate solutions for the Fourth industrial Revolution.

Duration: 30 Engagement hours
10 Modules:
1 Final Project

  • Intricacies of Fourth Industrial Revolution (4IR) and STEM Pedagogy
  • Preparing Visual Flowchart Software tool for algorithm programming Activities
  • Computational Thinking Console and Virtual algorithm programming activities
  • Computational Thinking Machine learning algorithm programming Activities
  • Physical computing for innovation applying DESIGN THINKING processes
  • Building real-world prototype Digital Input/Output smart applications
  • Building real-world prototype Analog Input/Output smart applications
  • Building real-world prototype Robotic applications
  • Building real-world prototype Smart Sensor for IOT applications
  • Preparing IOT Gateway and Cloud base Platform for Data collection, Visualization and Analytics
  • Final Project: IOT Integrated Preventive and Predictive maintenance system for manufacturing industry

IOT Device design Architecture & Development

IOT Device design Architecture & Development involves hardware platform, IOT network Architecture, Industrial IOT Cloud platform and Data transmission using HTTP & MQTT protocols. Participants will be engaged in rigorous Hands-On activities building hardware systems and programming using C/C++ to design and develop an Embedded Controller for EDGE and IOT Gateway/Node devices using ATMEGA 2560 microcontroller, Electronics, sensors.

Duration: 40 Engagement hours
10 Modules:
1 Final Project

  • Demystifying IOT
  • Working with Programming Algorithm and AI Algorithm models
  • Introduction a PC base IOT Gateway
  • Prepare Software, Microcontroller & Sensors for IOT Physical Computing
  • Embedded Controller and C/C++ programming
  • Developing an EDGE Embedded controller and Control System
  • Developing rapid Mobile APP for IOT EDGE controller interface
  • Developing a Prototype IOT Gateway/Node with WIFI & GSM Connectivity
  • Develop IOT Gateway/Node firmware for MQTT Data transmission
  • Design IOT Dashboard using MQTT Cloud industrial IOT Platform
  • Final Project: AIOT Integrated Fleet Management System

Sensor Data Visualization and Analytics with Cloud Server

Sensor data analytics is going to play an integral role in an Industries’ success. Whether it is Manufacturing, Oil & Gas or Agriculture, the future of all industries will be highly dependent on sensors – IIOT devices able to collect information from sensors to be stored in database and fed into data analytics platforms for further processing. In this training participants will develop an end-to-end solution from IIOT device to cloud data analytics platform on cloud server for real-time data collection and analytics.

Duration: 40 Engagement hours
10 Modules:
1 Final Project

  • Sensor Technology Overview
  • Working with Embedded microcontroller and sensors
  • Building Embedded IOT Gateway and Sensor node
  • Developing Embedded IOT Gateway and Sensor node firmware with C/C++
  • Cloud Server overview
  • Setting up SQL cloud server database for Sensor data collection
  • Working with PHP script on cloud server to collect sensor data from IOT devices
  • Working with Telemetry data table for basic statistical data analytics
  • Working with PHP, HTML, CSS and Json script to develop mobile APP friendly WEB IOT platform for Sensor data visualisation and Analytics
  • AIOT fundamental integration to develop intelligence notification and reporting
  • Final Project: IOT based Prevention and predictive maintained system for health care industry.

AI Fundamentals

This artificial intelligence fundamental is to offer an overview of AI concepts & workflows, along with the fundamentals of machine learning and deep learning. Learn AI along by working on specific use cases & learn the difference between supervised, unsupervised, & reinforcement learning. This training is the prerequisite for anyone who which to embark into Data science solutions and AI development.

Duration: 24 Engagement hours
4 Modules:
4 Assessment Quizzes

  • Decoding Artificial intelligence
  • Fundamental of Machine Learning and Deep learning
  • Machine Learning Workflow
  • Performance metrics in AI

Statistics for Data Science

Data plays a huge role in today’s tech world. All technologies are data-driven, and humongous amounts of data are produced on a daily basis. Training in Statics for Data Science enable able one to analyze data sources, clean and process the data, understand why and how such data has been generated, take insights from it, and make changes such that they profit the organization. This training is the prerequisite for anyone who which to embark into Data science solutions and AI development.

Duration: 30 Engagement hours
10 Modules:
2 Assessment Quizzes,
1 Practical Test

  • Introduction to Statistics
  • Sample and Population
  • Descriptive Statistics
  • Measure of central tendency
  • Distributors
  • Estimators and Estimates
  • Inferential Statistics
  • Regression analysis
  • Assumptions of linear Regression analysis
  • Categorial Data

Python for Data Science

Beginner-friendly introduction to Python and Python for data science, as well as python programming in general. Python being of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries. This training is the prerequisite for anyone who which work on Data Science with phyton programming language.

Duration: 60 Engagement hours
5 Modules:
4 Assessment Quiz,
1 Practical project

  • Python Basics
  • Python Data Structure
  • Python programming fundamentals
  • Working Data in Python
  • Working NumPy arrays

Data Science with Python

The Data Science with Python enable one to master the concepts of Python programming. Through this Data Science with Python training, one will learn Data Analysis, Machine Learning, Data Visualization, Web Scraping, & NLP. Key take away from this training, one will master the essential tools of Data Science with Python for AI development.

Duration: 72 Engagement hours
12 Modules:
6 Assessment Quiz,
2 Practical projects

  • Data Science Overview
  • Data Analytics Overview
  • Statical Analysis for Business Application
  • Python Environmental setup and essentials
  • Mathematical Computing with NumPy
  • Scientific Computing with SciPy
  • Data Manipulations with pandas
  • Machine Learning with SciKit-Learn
  • Natural language processing with Scikit-Learn
  • Data Visualization wit matplotlib
  • Web scraping with BeautifulScoup
  • Python integration Hadoop MapReduce and Spark

Machine Learning

Machine learning: the branch of AI, based on the concept that machines and systems can analyse and understand data, and learn from it and make decisions with minimal to zero human intervention. Most industries and businesses working with massive amounts of data have recognized the value of machine learning technology. By examining the insights from this data, businesses are able to work more efficiently and gain an advantage over others.

Duration: 60 Engagement hours
10 Modules:
6 Assessment Quiz,
2 Practical projects

  • Introduction AI and Machine Learning
  • Data Processing
  • Supervised learning
  • Feature Engineering
  • Supervised Learning Classification
  • Unsupervised Learning
  • Time Series Modeling
  • Ensemble learning
  • Recommender Systems
  • Text mining