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Artificial Intelligence (Deep Learning & Computer Vision Focused) Training

PKR. 30,000

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Learn AI algorithms through Tensor flow & Python advanced language.
Start Date
Nov 18, 2023
End Date
Jan 07, 2024
Timing
11:00 AM-04:00 PM
Location
Online
Type
Instructor Led
Duration
80 Hours
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Overview

Computer vision is a rapidly growing field in which machines are able to interpret and process visual information. This field has been enabled by advances in machine learning, deep learning and image processing.

Computer vision is used to build systems that are able to recognize objects, identify patterns and make decisions based on the visual data. It is used for applications such as autonomous vehicles, facial recognition, robotics, medical imaging and more.

With the right training and understanding, computer vision can be used to create powerful applications that are able to see and understand the world around them.

Tools Covered

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  • Familiarity with AI Tools and Technologies: Participants will be exposed to various AI tools and technologies, such as TensorFlow, Jupyter and OpenCV, and will learn how to use them to develop AI models and applications.
  • Hands-on Experience with AI Projects: Participants will engage in practical exercises and real-world projects, allowing them to apply their learning to build AI models, train them with data, and evaluate their performance. This will help them gain practical experience in developing AI applications.
  • Computer Vision: Participants will learn the basics of computer vision, including image processing, object detection, image segmentation, and facial recognition. They will also learn how to build computer vision applications using AI techniques, such as convolutional neural networks (CNNs).

  • Anyone who has an interest in Deep Learning, Computer Vision and its applications and is looking forward to further explore these domains to either extend their skillset for career opportunities or to simply learn about Computer Vision Systems.

Meet the Instructors

Ahmad Tariq

Data Scientist | Machine Learning | Deep Learning | Computer Vision

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Course Outline

Ahmad Tariq

Data Scientist | Machine Learning | Deep Learning | Computer Vision

Experienced Data Scientist with a working experience in the Telecom & FinTech industry. Successfully delivered multiple projects to international and national clients.

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Course Outline

Abdul Rahman

Machine Learning Engineer @ Redmarker Systems

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Course Outline

Abdul Rahman

Machine Learning Engineer @ Redmarker Systems

A highly skilled and experienced machine learning engineer with a strong background in developing and implementing cutting-edge machine learning algorithms and models.

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Course Outline

Course Outline

  • Introduction to Python
  • Python Variables and Data Types
  • Control Structures
  • Functions
  • Lists and Data Structures
  • File Handling
  • Common Python Libraries
  • Understanding errors in Python

  • Open CV
  • Basics of Impage Processing
  • Read Image
  • Image Matrix
  • Threshold, Multiplication
  • Gradients
  • Resolution of Image
  • What is Video
  • Frames Per Second
  • Different Video Streaming Protocols

  • Neural Network – Single Node
  • Multilayer Perceptrons
  • Forward Propagation\ Backward Propagation
  • Optimizers
  • Evaluation Metrics, Hyperparameter Tuning
  • Image Classification Project – live demonstration

  • CNN Introduction + Background + Applications
  • Different layers (Each layer explained in depth)
  • Parameters/ Hyperparameters + Optimizers + Side concepts
  • Making a CNN in Python with Tensorflow
  • Image Classification Project – live demonstration
  • CNN Variants

  • Transfer learning
  • VGG network
  • RESNET network
  • Inception v1, v2, v3
  • Autoencoders
  • Section introduction

  • Section introduction
  • Object localization
  • Object detection
  • Problem of scale and shape
  • Retina net
  • IOU and non-max suppression
  • RCNN model family and its limitiations
  • Yolo
  • Project : Custom object detector

  • Simple face recognition 1: Faces in wild (use PCA, SVM)
  • Simple face recognition 2: using DLIB and KNN/SVM
  • FaceNet by Google
  • MTCNN
  • Project: Custom Face Detection and Recognition

  • Introduction and Applications
  • Generator and Discriminator
  • Project 1: create MNIST like dataset
  • PIX2PIX and Cycle GAN
  • Project 2: Satelite image to Google map like image translation

Our Methodology

Industry Usecases

With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

Technical Support

Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you and keeping you on track.

Career Mentorship

You’ll have access to resume support, portfolio review and optimization to help you advance your career and land a high-paying role.

Frequently Asked Questions

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Duration: 8 weeks (Sat-Sun)
Timings: 11AM – 4PM

Since our courses are led by Industry Experts so it is made sure that content covered in course is designed with hands-on knowledge of more than 70-75 % along with supporting theory.

Yes, you can rejoin the training within the span of an year of your registration. Please note following conditions in case you’re rejoining.
1) There are only 5 seats specified for rejoiners in each iteration.
2) These seats will be served on first come first basis
3) If you have not submitted your complete fee, you may not be able to rejoin. Your registration would be canceled

Don’t worry! We have got you covered. You shall be shared recorded lectures after each session, in case you want to revise your concepts or miss the lecture due to some personal or professional commitments

During the lectures, there will be demonstration and practical implementation of the concepts taught in the lectures. The participants would be encouraged to follow

This Certification Training course includes multiple real-time, industry-based projects, which will hone your skills as per current industry standards and prepare you for the future career needs.
Different projects which will give the students applied knowledge to different computer vision problems taught in the lectures and the working behind them, using public datasets.

Yes,  you will be awarded with a course completion certificate by Dice Analytics. We also keenly conduct an annual convocation for the appreciation and recognition of our students

Since our instructors are industry experts so they do train the students about practical world and also recommend the shinning students in industry for relevant positions. 

For this professional course, you need to have a PC with minimum 4GB RAM and ideally 8GB RAM .
So, what's your plan?

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