Machine Learning

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Course: Certificate Course in Machine Learning (basic to intermediate Level)

Organized at India Jordan Center of Excellence in Information Technology (IJCoEIT) and endorsed by INT@J

 

Course Overview

  • To master the fundamentals of writing Python scripts, Data Types, Variables, Operators, Input/output, variables, data types, Flow of Control, looping, Lists, Dictionaries, sets, functions, and classes.
  • Describe the various types of Machine Learning algorithms and when to use them.
  • Learn Mathematics of Linear Algebra, Matrices, and statistics for Data Science and Machine Learning.
  • Understand the full product workflow for the machine learning lifecycle.
  • Learn to how pre-process data, clean data, analyze your own data sets and gain insights through data science.
  • Feature engineering techniques, including imputation, outliers, binning, and normalization
  • Explore large datasets using data visualization tools like Matplotlib and Seaborn.
  • Learn how to use Scikit-learn to apply powerful machine learning algorithms.
  • Learn which Machine Learning model to choose for each type of problem.
  • Implement, evaluating and improving Machine Learning models [Supervised and unsupervised].
  • Use train/test and K-Fold cross validation to choose and tune your model.
  • Learn best practices for real-world data sets.
  • Get complete understanding of deep learning using Keras and Tensorflow.
  • Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications.
  • Understand convolution and why it’s useful for Deep Learning
  • Understand and explain the architecture of a convolutional neural network (CNN)
  • Implement a CNN in TensorFlow 2.
  • Apply CNNs to for Image classification tasks.

Career preparation

Accepted students will gain an access to e – content designed by C-DAC. also extra material that are prepared by the instructor will be shared.

By the end of the Certificate Course in Machine learning the students will gain practical, hands-on experience preparing them for a career as a machine learning engineer, data scientist using python, data analyst, machine learning researcher, and machine learning specialist.

After successfully completing this course, certified students will have an opportunity for a job interview for employment in one of the local related companies.

Learning components

  • Class topics:
  1. Programming using python.
  2. Mathematics of Linear Algebra, Matrices, and statistics for Data Science and Machine Learning.
  3. Feature engineering.
  4. Exploratory data analysis (EDA).
  5. Machine learning.
  6. Tensor flow.
  7. Deep learning and convolutional neural network
  • Hands-on labs, exercises, and quizzes to reinforce learning.
  • Exams to measure learning outcomes.

Course Eligibility

  • A Candidate at least must be a bachelor’s degree holder in the computing field or any other relevant discipline.
  • A candidate can be in their last year of study.
  • Candidates must have a minimum GPA of 60% in BSc.

Number of seats: 20

Selection criteria

  • Candidates who have scored above 90% GPA are given priority.
  • Candidates who have python programming knowledge are given priority.
  • Candidates who work on jupyter notebook, google-colab ,and kaggle are given priority.

Start and End Date: 6th of July to 5th of October 2024 (every Saturday (10:30 – 16:30), Monday (17:30 – 20:30) and Wednesday (17:30 – 20:30).

Fees: 500 JD

ABOUT THE INSTRUCTOR ( ENG MO’TASEM SAMMARA)

Mo’tasem Samara is a seasoned computer engineer with 15+ experience, holds a master’s degree in computer engineering /embedded systems from Yarmouk university.

He is an assistant instructor at computer and information college at Jordan University of science and technology (JUST).

In his current role, Mo’tasem taught a variety of courses such as scripting languages, digital logic design, object-oriented software analysis and design, microprocessor systems, software design and development project, artificial intelligence, and more.

He is a master trainer in machine learning certified from Center for Development of Advance Computing (C-DAC) India.

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