Course List

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IR4.0 Foundation Course

IR4.0 Foundation Course

  • Business
  • Stephanie
  • 37 Lectures
  • 2800 students
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Data analysis with python to fuel AI applications

  • Business
  • Stephanie
  • 37 Lectures
  • 3768 students
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Data Visualization with python to fuel AI applications

  • Business
  • Stephanie
  • 37 Lectures
  • 3372 students
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Unveiling ML Algorithm Implementation

  • Business
  • Stephanie
  • 37 Lectures
  • 3241 students
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Deep Learning Fundamentals & Computer Vision Insight

  • Business
  • Stephanie
  • 37 Lectures
  • 3346 students
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Moving ahead with cloud

  • Business
  • Stephanie
  • 37 Lectures
  • 3242 students
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Learning through cloud core services

  • Business
  • Stephanie
  • 37 Lectures
  • 3252 students
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Building databases through cloud services

  • Business
  • Stephanie
  • 37 Lectures
  • 3203 students
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Learning through cloud cognitive services

  • Business
  • Stephanie
  • 37 Lectures
  • 3156 students
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Understanding Cloud Modern Applications

  • Business
  • Stephanie
  • 37 Lectures
  • 3257 students
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Fundamentals of Web Technologies

  • Business
  • Stephanie
  • 37 Lectures
  • 3479 students
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Building blocks of Business Logic

  • Business
  • Stephanie
  • 37 Lectures
  • 3334 students
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Database Connectivity with Server

  • Business
  • Stephanie
  • 37 Lectures
  • 3463 students
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Getting started with ReactJS

  • Business
  • Stephanie
  • 37 Lectures
  • 3637 students
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Moving Ahead with Spring Framework

  • Business
  • Stephanie
  • 37 Lectures
  • 3540 students
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Fundamentals of Operating System and Database

  • Business
  • Stephanie
  • 37 Lectures
  • 3670 students
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Understanding the Front-end Development

  • Business
  • Stephanie
  • 37 Lectures
  • 3986 students
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Foundation course on Java Programming

  • Business
  • Stephanie
  • 37 Lectures
  • 4379 students
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Fundamentals of Cloud Computing

  • Business
  • Stephanie
  • 37 Lectures
  • 5330 students
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Foundation Course on Generative AI

  • Business
  • Stephanie
  • 37 Lectures
  • 15975 students
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P1 - Implementation of ML model for image classification

This project presents the implementation of a machine learning model for image classification using Convolutional Neural Networks (CNNs). We investigate the effectiveness of CNN architectures in recognizing and categorizing images across multiple classes. The project involves a comprehensive approach, beginning with data acquisition and preprocessing to enhance image quality and ensure uniformity.

  • Business
  • Stephanie
  • 37 Lectures
  • 563 students
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P2 - Attendance Management System using Face Recognition

This project presents the development of an Attendance Management System utilizing face recognition technology to streamline the process of attendance tracking in educational and corporate environments. The system aims to reduce manual errors, improve attendance accuracy, and ensure the authenticity of student/staff attendance in classrooms or workplaces.​

  • Business
  • Stephanie
  • 37 Lectures
  • 1011 students
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P3 - Spam Email Classification using NLP and Machine Learning

This project focuses on the development of a Spam Email Classification system utilizing Natural Language Processing (NLP) and machine learning techniques to enhance email security and user experience. The system aims to effectively distinguish between legitimate and spam emails by analyzing textual content and identifying key linguistic patterns.

  • Business
  • Stephanie
  • 37 Lectures
  • 505 students
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P4 - Implementation of Chatbot using NLP

This project presents the implementation of a chatbot using Natural Language Processing (NLP) to enhance user interaction and provide automated responses in various domains, including customer service, education, and healthcare. The chatbot leverages advanced NLP techniques to understand user queries, interpret context, and generate relevant responses. We detail the architecture, which incorporates intent recognition, entity extraction, and dialogue management, enabling the system to engage in meaningful conversations.

  • Business
  • Stephanie
  • 37 Lectures
  • 831 students
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P1- SMS Spam Detection System Using NLP

Imagine you receive a large number of SMS messages every day. Sorting through each message to separate important ones from spam manually would be overwhelming. Using a machine learning model, you can automate this process and ensure that only relevant SMS messages capture your attention.

  • Business
  • Stephanie
  • 37 Lectures
  • 546 students
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P2 - Plant Disease Detection System for Sustainable Agriculture

The problem lies in the difficulty of identifying plant diseases early, which often leads to the overuse of chemicals and inefficient farming practices. To solve this, there is a need for an intelligent and automated system that uses computer vision and machine learning to detect diseases in real-time. This system would help farmers take quick and targeted actions, promoting sustainable farming by reducing chemical usage and protecting crops effectively.

  • Business
  • Stephanie
  • 37 Lectures
  • 290 students
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P3 - Identifying Shopping Trends using Data Analysis

Retail businesses accumulate vast amounts of shopping data from multiple channels (in-store, online, etc.), but struggle to effectively analyze this data to identify emerging trends, customer preferences, and seasonal buying patterns.​ Failure to identify and act on shopping trends could result in lost revenue, overstock or stockouts, ineffective marketing strategies, and an inability to maintain competitive advantage in the retail market.

  • Business
  • Stephanie
  • 37 Lectures
  • 521 students
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P4 - Human Pose Estimation using Machine Learning

Understanding human movements and body postures is a complex task, particularly in fields like sports, healthcare, and surveillance. Without automated systems like Human Pose Estimation, activities such as motion analysis and injury prevention rely on manual methods, which are often slow, labor-intensive, and prone to errors. This creates a need for efficient and accurate solutions that can address these challenges effectively.​

  • Business
  • Stephanie
  • 37 Lectures
  • 393 students