Advanced

Machine Learning with Python

online png Online
18+ years
Fees png Course fees cover 12 sessions over 3 months
Group course

price svg
$200
/ 3 months
 



Private course

price svg
$450
/ 3 months
 
Program Description
Machine learning is a subset of Artificial Intelligence. It is also a ground-breaking technology that has powered some of our most important applications in the last few years. Machine Learning powers social media feeds, voice-activated assistants, facial recognition technology, chatbots, and recommendation systems. In this Machine Learning course, you will learn about several machine learning algorithms, such as linear regression, random forests, and SVMs. You will also learn about important Machine Learning concepts such as overfitting, underfitting, and parameter tuning. Then, you will implement these algorithms using the Python programming language. More importantly, you will gain the knowledge needed to apply these algorithms to various real-life machine learning problems.
Learning Outcomes
  • lo en Write python code that implements Machine Learning algorithms such as linear regression, random forests, and SVMs
  • lo en Use the workflow of Machine Learning experts from data collection to deploying models
  • lo en Understand what machine learning is and how it is used in the real world
  • lo en Differentiate between supervised and unsupervised learning
  • lo en Save machine learning models to be used by others
Course fees cover:
  • lo check 12 hours of live online sessions with Geek Express Certified Trainers
  • lo check Geek Express certification accredited by STEM.org & KHDA Dubai
  • lo check Final project development
  • lo check Digital portfolio access with automatic attendance and progress reporting
  • lo check Access to Geek Express app
Private or Group?
Upon booking the course, you can choose between private or group sessions. Private courses start immediately after you book, at the time and date of your choice. Group classes start directly after 3 students register for the course (Maximum waiting time: 2 weeks)