In this course, we’ll learn about more advanced machine learning methods that are used to tackle problems in the supply chain. We’ll start with an overview of the different ML paradigms (regression/classification) and where the latest models fit into these breakdowns. Then, we’ll dive deeper into some of the specific techniques and use cases such as using neural networks to predict product demand and random forests to classify products. An important part to using these models is understanding their assumptions and required preprocessing steps. We’ll end with a project incorporating advanced techniques with an image classification problem to find faulty products coming out of a machine..
APPROVED FEES FOR ACADEMIC SESSION
Tuition Fee .............................................................................................NGN 250,000
Admission Application...........................................................................NGN 5,000
NB: Excursion (Tour) will be organized to exposed all students to aspect of the industry on one or two occasions during the profane , student should be prepared for.
MODE OF PAYMENT
Installment in payment is allowed, all payment should be completed before examination.
Admission into class/department will be subject to first come first served.
ACCOUNT DETAIL :
Bank Name:............................................................... Access Bank Plc
Account Name :.........................................................ABTECH SCHOOL OF AVIATION AND MARITIME
Account Number:.......................................................1565826913
DAYS
HOURS
MINUTES
SECONDS
Event Details
Full-Time I Part-Time I Weekend Class I
Online Class
- TOTAL COST
NGN 250,000
- DURATION
3 WEEKS
- START TIME
11 : 30 AM
- END TIME
3 : 00 PM
- LOCATION
ABUJA I LAGOS
Course Outlines
- Machine Learning in the Supply Chain
- In this module, we’ll learn about the use cases of machine learning in the supply chain. We’ll start with the big picture applications before diving deeper into specific algorithms, including neural networks. Throughout the module, we’ll explain not only the general artificial intelligence concepts and mathematics, but also how these algorithms can specifically be used for the supply chain.
- A Classical AI Approach
- In this module, we’ll cover the concepts relating to the ML paradigm. We’ll start by learning how to pick a model, relying on considerations such as managing the bias-variance tradeoff. Next, we’ll explore how machine learning models converge, including the use of stochastic gradient descent to minimize loss functions. Finally, we’ll end with some practical considerations on coding advanced AI models with libraries for hyperparamter tuning.
- Images and Text
- In this module, we’ll expand beyond numbers and learn how to use machine learning on images and text. We’ll start by talking about how to analyze text data and cover the primary methods behind natural language processing. Then, we’ll learn how to analyze images by constructing convolutional neural networks complete with convolutions and pooling layers.
- Final Project: Detecting Anomalies with Image Classification
- In this final project, we’ll apply what we learned in the last module to classify images of products based on whether there is a defect or not.
- Â
Abuja Office:
Suite A 28 Hawthorn Suite, 1 Uke Street off Amadu Bellow Way Garki Area 11 Abuja FCT.
Lagos Office:
Suite 10 Amazing Grace Plaza,34 Sule Street Idi-Mangoro Ikeja Lagos State .
