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Students will start by attending the weekly class at the scheduled time to get to know the facilitators and peers.
Learning more deeply and thoroughly with Artificial Intelligence (AI) and make related projects with the new interesting knowledge.
In Program G, students will be able to learn Artificial Intelligence (AI) and make related projects. They will be able to know the process of Machine Learning from getting data, converting data, training the machine with suitable model and testing for output. Moreover, they are exposed to Natural Language Processing, Text Recognition, Image Recognition and many more AI-related projects.
This program is exclusively designed for students to learn AI concepts such as Machine learning, Deep Learning, Text Recognition, Image Recognition, etc. At the same time, they can create many AI-related projects via different Python AI libraries.
Theme 1 : AI Fundamentals
Chapter 1 : Artificial Intelligence (AI)
Chapter 2 : Machine Learning
Theme 2 : Natural Language Processing (NLP) with Scikit-Learn
Chapter 3 : Scikit-Learn
Chapter 4 : Natural Language Processing (NLP)
Chapter 5 : Text Processing
Chapter 6 : KNN and Popular Classifiers
Theme 3 : Artificial Neural Network (ANN) with TensorFlow
Chapter 7 : Artificial Neural Network (ANN)
Chapter 8 : Image Classification
Chapter 9 : Image Classification Process with TensorFlow
Chapter 10 : Convolutional Neural Network (CNN) with Tensorflow
Theme 4 : Computer Vision with OpenCV
Chapter 11 : Computer Vision
Chapter 12 : OpenCV-Python
Chapter 13 : Drawing with OpenCV
Chapter 14 : Haar-cascade Detection in OpenCV
Chapter 15 : Object Detection using Haar Cascades Classifier
Create a chatbot to chat with you! You can train your chatbot to learn human chat and reply with suitable responses. All this can be done by using the Natural Language Processing techniques and Python package: Scikit Learn.
Create a model to classify Human Hand Gesture. You can train your model to identify the image and classify the image into the correct category. All this can be done by using the Image Classification techniques and Python package: TensorFlow.
Create a model to detect human faces on an image or video. You train your model to identify human faces and show the output on the image. All this can be done by using the Object Detection techniques and Python package: OpenCV-Python.
Students will start by attending the weekly class at the scheduled time to get to know the facilitators and peers.
Join the class sessions with your instructor and peers. The main instructor will give lectures on the topic learned.
If you need further support or information about the classes, exercises and projects, talk to our instructors to answer your questions in mind.
Students can easily access the lesson materials including pre-recorded lesson videos and lesson notes to do better self-preparation before entering the class.
Practice the new skills by completing the projects and challenges with the respective instructors. Our instructors will provide feedback and guide the students.
Telebort experience ends with graduation so that you can see your class's work, showcase your work, and receive a certificate and academic transcript upon completion of the program!
Telebort's Computer Science Education Roadmap is designed with STEAM education for school children to express their own ideas in designing their own stories, mobile apps, websites and many more.
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