Machine Learning with Python

BY
IBM via Coursera

Master key skills in Machine Learning using the highly-popular Python programming language by enrolling for Machine Learning with Python offered by IBM.

Lavel

Intermediate

Mode

Online

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

The Machine Learning with Python certification course offered by IBM is a comprehensive program designed to introduce learners to the basics of machine learning using the Python programming language. Machine Learning with Python programme offered by IBM is the 13 hours (approx.) duration certification course having 6 moudules in total where students can learn on their own pace.

The Machine Learning with Python  certification course, offered by IBM via Coursera, is the intermediate level programme where students will learn classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression. You’ll also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN.  Machine Learning with Python certification course offered by IBM helps the students to learn new concepts from industry experts and develop job-relevant skills with hands-on projects along with shareable career certificate from IBM.


The highlights

  • Offered by IBM
  • 100% online mode of learning
  • Learning with IBM instructors
  • Approximately 13 hours of videos and readings
  • Flexible deadlines in accordance with your schedule
  • Shareable certificate for online profile/CV
  • IBM Digital Badge upon completion

Program offerings

  • Audio-visual
  • Course resources and readings
  • Shareable certificate
  • Interactive quizzes

Course and certificate fees

The fees for the course Machine Learning with Python is -

HeadAmount in INR
1 month (20+ hours/week)
Rs. 4,115
3 month (14+ hours/week)
Rs. 8,230
6 month (7+ hours/week)
Rs. 12,345

 

certificate availability

Yes

certificate providing authority

Coursera +1 more

What you will learn

Machine learning Knowledge of python Knowledge of scikit-learn

Upon completion of Machine Learning with Python certification course offered by IBM , the participants will be able to learn about the description of the various types of Machine Learning algorithms and when to use them  and comparing and contrasting linear classification methods, including multiclass prediction, support vector machines, and logistic regression.

Students will also get knowldege about how to write Python code that implements various classification techniques, including K-Nearest neighbors (KNN), decision trees, and regression trees and to evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation metrics after completing Machine Learning with Python certification course offered by IBM via Coursera.

The syllabus

Module 1: Introduction to Machine Learning

Videos
  • Course Introduction
  • Welcome
  • Introduction to Machine Learning
  • Python for Machine Learning
  • Supervised vs Unsupervised
Quiz
  • Practice Quiz: Intro to Machine Learning
  • Graded Quiz: Intro to Machine Learning

Module 2: Regression

Videos
  • Introduction to Regression
  • Simple Linear Regression
  • Model Evaluation in Regression Models
  • Evaluation Metrics in Regression Models
  • Multiple Linear Regression
Readings
  • Errata for "Evaluation Matrix in Regression Model" Video
  • Errata: Simple Linear Regression Video
  • Errata: Multiple Linear Regression Video
Quizzes
  • Practice Quiz: Regression
  • Graded Quiz: Regression
app items
  • Lab: Simple Linear Regression
  • Lab: Multiple Linear Regression

Module 3: Classification

Videos
  • Introduction to Classification
  • K-Nearest Neighbours
  • Evaluation Metrics in Classification
  • Introduction to Decision Trees
  • Building Decision Trees
Reading
  • Regression Trees
Quizzes
  • Practice Quiz: Classification
  • Graded Quiz: Classification
app items
  • Lab: KNN
  • Lab: Decision Trees
  • (Optional) Lab: Faster Credit Card Fraud Detection using Snap ML
  • Lab: Regression Trees
  • (Optional) Lab: Faster Taxi Tip Prediction using Snap ML

Module 4: Linear Classification

Videos
  • Intro to Logistic Regression
  • Logistic regression vs Linear regression
  • Logistic Regression Training
  • Support Vector Machine
Reading
  • Multiclass Prediction
quizzes
  • Practice Quiz: Linear Classification
  • Graded Quiz: Linear Classification
app items
  • Lab: Logistic Regression
  • Lab: SVM (Support Vector Machines)
  • Lab: Multiclass Prediction
plugin
  • GridSearchCV: Hyperparameter Tuning in Machine Learning

Module 5: Clustering

Videos
  • Intro to Clustering
  • Intro to k-Means
  • More on k-Means
quizzes
  • Practice Quiz: Clustering
  • Graded Quiz: Clustering
app item
  • Lab: k-Means

Module 6: Final Exam and Project

readings
  • Congratulations
  • IBM Digital Badge
  • Project Scenario
Quiz
  • Final Exam
peer review
  • Submit Your Work and Review Your Peers
app item
  • Lab: Rain Prediction in Australia

Instructors

Mr Joseph Santarcangelo

Mr Joseph Santarcangelo
Data Scientist
IBM

Ph.D

Mr Saeed Aghabozorgi

Mr Saeed Aghabozorgi
Senior Data Scientist
IBM

Ph.D

FAQs

None

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