Machine Learning With Python Course

Start Date:
TBD
60
academic hours
Final Project
Machine Learning with Python

Machine Learning With Python Course

Artificial Intelligence (AI) is gaining more and more significance in our lives over time, essentially reshaping the world with a new array of options and capabilities offered by computers, providing us with solutions that were not conceivable in the past across a vast range of domains.

Through the use of Machine Learning, we can preserve the information we generate and accumulate in all aspects of our lives and activities, enabling us to process this data and extract insights and conclusions from it.

The Python programming language has highly essential advantages that make it the preferred language for numerous projects in the field of artificial intelligence. Consequently, it's evident that more and more startups and companies are developing Machine Learning algorithms using Python. Due to its widespread usage, there is a high demand in the market for experienced developers who are skilled in working with Python in the field of artificial intelligence development.

The Machine Learning Development Using Python course includes:

  • Frontal lectures with a strong emphasis on practical exercises.
  • Classroom exercises accompanied by explanations, homework assignments, and solutions on the course website.
  • Course booklet.
  • Videos and presentations on the course website.
  • Lectures take place once a week in the evening hours.

Who is the Machine Learning Development Using Python course suitable for?

  • College/university graduates who wish to specialize in developing artificial intelligence systems.
  • Hardware/software/computer science engineers with no experience in this field who are interested in professional reorientation.
  • Individuals with relevant background and previous experience, including Python programming and working with Linux operating systems.

Our curriculum combines knowledge and practical exercises (a lot of practical exercises) and is comprehensive. The course lessons are focused on the practical knowledge and skills required for the field, developed in collaboration with technology companies in the industry, and are constantly updated according to projects in our development division.

Course Structure

Ch. 1

Introduction to Machine Learning

Ch. 2

Machine Learning Mathematical tools

Ch. 3

Linear Algebra (using Scipy)

Ch. 4

Statistics

Ch. 5

Confusion Matrix, ROC

Ch. 6

Machine Learning Software Tools

Ch. 7

Using Jupyter Notebook

Ch. 8

Model Deployment

Ch. 9

Working with Cloud

Ch. 10

Working with Data-Bases

Ch. 11

Implementing Machine Learning with Python

Ch. 12

Data preprocessing, data exploration

Ch. 13

Data modeling, model evaluation

Ch. 14

Cross Validation

Ch. 15

Decision Trees

Ch. 16

SVM

Ch. 17

Time series, Anomaly Detection

Head of the department
teacher-image-Alex-Shoihat

Meet your instructor

Alex Shoihat

Head of Machine Learning

Alex holds a B.Sc. in Information Systems and an M.A. in Electrical and Electronic Engineering.

As a Machine Learning Engineer at Embedded Academy, Alex specializes in the field of artificial intelligence, applying over 13 years of experience in project development, management, and transitioning from development to production in various domains such as Linux Embedded.

Throughout his career, Alex developed his expertise working with the integration of Machine Learning and Deep Learning in the Computer Vision and Data Analysis field.

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