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PMMD 2001

2.50(2)

PMMD 2001

  • Course level: Beginner

About Course

This beginner's course requires a background of Senior Secondary Trigonometry, Calculus, and a decent ability to navigate the web. It is a practical skills course suitable for students in full-time study elsewhere but want to gain the necessary skills to become competitive in a globalized world. You will need to invest in a computer and decent data bandwidth. Most software used are in the public domain or available to students for free.

Description

This package is for individual registration. A group of 4 people or less will pay N10,000.00 each per month.

This course covers:

• Programming, Design & AI
• Python Lexical Analysis with Geometrical visualizations;
• Fusion 360 Basics;
• Introduction to Machine Learning;
• Fundamental types and the Python Object Model;
• Programme Structure, Execution & Debugging;
• The Fusion 360 API Object Model and Parametric Modeling.
• Models for simulation scenarios and design

 

Topics for this course

48 Lessons60h

Python: Modeling, Machine Learning & Design

Design Lecture Series: Python for Modeling, Machine Learning & Design
Lecture 001: Python for Modeling, Machine Learning & Design: Pre-Lecture Guide
Lecture 011: Introducing Machine Learning1:30:31
Lecture 012: Lexical Analysis1:44:02
Tutorial 012: Lexical Analysis00:54:10
Lecture 021: Python Collections and Controls1:40:54
Lecture 022: Supervised Learning1:27:47
Tutorial 021: Python Collections and Controls I1:14:34
Tutorial 022: Supervised Learning46:50
Lecture 031: Python Collections and Controls I Review00:53:53
Lecture 032: Python Collections and Controls I Tutorial Review52:57
Lecture 033: Python Collections and Controls II1:21:34
Tutorial 031: Python Collections and Controls II00:49:13
Tutorial 032: Perceptron Algorithm44:12
Lecture 041: Unsupervised Learning1:35:44
Lecture 042: Python Collections and Controls III1:43:43
Tutorial 041: Unsupervised Learning1:08:11
Tutorial 042: Python Collections and Controls III00:33:44
Lecture 051: Unsupervised Learning II1:36:27
Lecture 052: Simple Models in Fusion 360 API1:28:25
Tutorial 051: Simple Models in Fusion 360 API52:25
Tutorial 052: Unsupervised Learning II33:35
Assignment 050: Simple Models in Fusion 360 API
Lecture 061: Simple Models in Fusion 360 API II1:45:39
Tutorial 061: Simple Models in Fusion 360 API II49:46
Tutorial 062: KMeans Clustering47:46
Lecture 071: Simple Models in Fusion 360 API III1:12:44
Tutorial 071: Collections and Comprehensions26:44
Tutorial 072: Machine Learning Recap38:55
Lecture 081: Object-Oriented Python I38:01
Lecture 082: Machine Learning Recap II50:52
Tutorial 081: Object-Oriented Python I30:00
Tutorial 082: Machine Learning Recap II27:09
Lecture 091: Object-Oriented Python II-158:45
Lecture 091: Object-oriented Python II-200:34:20
Lecture 091: Object-Oriented Python II-326:23
Tutorial 091: Object-Oriented Python III1:04:38
Lecture 101: Distinguish Between Males and Females39:40
Tutorial 101: Distinguishing Between Males and Females34:20
Lecture 102: Fusion 360 Object Model1:03:21
Lecture 111: Distinguish Between Males and Females II1:40:38
Tutorial 1102:07:38
Lecture: 112: Fusion 360 Object Model II1:54:52
Lecture 121: Perceptron
Lecture 122: Fusion 360 Object Model III1:30:13
Tutorial 122: Fusion 360 Object Model III1:01:42

Student Feedback

2.5

Total 2 Ratings

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It was really great taking the course, i grew from being a novice in programming generally to one who can read ,write codes,and draw models of simple assembles(simple pully assemble) using both the API and GUI. The lecture --- tutorial structure of the course was very effective. A big thanks to the whole team

It's have been interesting to me as a mathematian. Thanks to this initiative

₦10,000.00