Python for Machine Learning Certification Master course

Name: Python for Machine Learning Certification Master course
Rating: 2.8 (2 reviews)

Learn Machine Learning using Python, Regression, Decision Trees, SVM, Numpy, Pandas, Scikit-Learn, Matplotlib streamlit

Created bySalvatore Aetos

Last updated 1/2025

English

What you'll learn

Use Python for Data Science and Machine Learning
Create Machine Learning projects webapp using streamlit
Learn to use Pandas for Data analysis
Implement Scikit-Learn for Machine Learning projects
Linear Regression
Learn to use Matplotlib for Python Plotting
Random Forest and Decision Trees
Support Vector Machines
Learn to use NumPy for Numerical Data

Course content

7 sections • 23 lectures • 3h 34m total length

Introduction2:24

Start-up Project4:05
Open Visual Studio Code and create a project folder with a data subfolder. Create a Python file named app.py and place salary_data.csv containing years of experience and salary data.
Installation of Python libraries10:24
Title and Navigation9:52
Build and run a salary predictor app using stream and pandas, with a sidebar navigation of home, prediction, and contribute pages and radio buttons for seamless switching.
Image and Load Data7:49
Interactive and Non-Interactive plots7:06
Import libraries and prepare data from a csv to build non-interactive and interactive scatter plots. Set axis labels for years of experience and salary, and render graphs in the app.
Graph plots adjusted10:44
Interactive slide connected to plots9:23
Prediction using Linear progression on Plots14:31
Changing Image1:37
Swap the home page image by replacing the file in the data folder and saving with ctrl+s, then revert to the original image by reloading the previous image file.
Contribution to Data (Primary Data as .CSV)19:46
Further tips on Python Streamlit3:51
Learn practical tips to troubleshoot python streamlit apps by ensuring python and the scripts directory are in your system path and setting environment variables so your computer recognizes installed libraries.

Project Setup and Streamlit Introduction4:00
Title and Side bar12:01
Build and run a streamline Python data app, set a title, auto update, load iris, breast cancer, and wine datasets, and add a sidebar with dropdowns and random forest classifier.
Shape of Datasets and Number of Classes9:21
Select Dataset and Keys11:23
Streamlit Classifiers and dealing with Errors15:36
Classifiers Accuracy Score8:13
Train and test a classifier on breast cancer, iris, and Lyme datasets, split data with test size 0.2, fit the model, predict, and evaluate accuracy score.
Plotting the Dataset8:00

Requirements

None

Description

Are you ready to start your career in Machine learning and as a Data Scientist. This course will be your guide to learning how to use the power of Python and the libraries to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

Get certified in Machine learning. Please send me your email in my inbox and I will forward you your certification after your assessment. Please give at least few weeks to a month to receive your certificate via email as it is a popular course.

It is a brilliant course where you will learn how to setup the project step by step from installation of python and the libraries to finished project. There are three projects that will allow you to use and implement supervise and unsupervise learning in the projects.

You will learn to create the following projects:

1. Salary Predictor

2. Classification Webapp

3. BMI Calculator

This course will allow you to utilise and implement several Machine learning libraries to these projects. The list are:

Streamlit

KNN Clustering

SVM
Numpy

Pandas

MatplotLib

Scikit-Learn

Furthermore, you will be able to assess your knowledge through doing a quiz on Streamlit and Machine Learning. Also, a challenge is set to create a BMI calculator. Solutions are given in text form and video for explanation.

So I invite you to join me, Developer Shack on an exciting journey into unlocking the secrets of Machine Learning for Data Science.

Who this course is for:

Machine Learning Enthusiasts
Data Scientist Enthusiasts

Python for Machine Learning Certification Master course

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 2min

Python Start-up Information1 lecture • 20min

Python Salary Predictor Project11 lectures • 1hr 39min

Machine learning Classifier project7 lectures • 1hr 9min

Challenge (Create a BMI calculator)2 lectures • 20min

Chat GPT1 lecture • 4min

Machine Learning and Streamlit Assessment0

Requirements

Description

Who this course is for: