ZO020 Deep Learning with Julia in Life Sciences

4 ECTS - 2-0 Duration (T+A)- 2. Semester- 2 National Credit
Information About Course

Information
Goal, Content & Resources
Course Learning Outcomes
Relation with Program Learning Outcome
Week Plan

Information

Unit INSTITUTE OF NATURAL AND APPLIED SCIENCES
ZOOTECHNICS (PhD)
Code ZO020
Name Deep Learning with Julia in Life Sciences
Term 2018-2019 Academic Year
Term Spring
Duration (T+A) 2-0 (T-A) (17 Week)
ECTS 4 ECTS
National Credit 2 National Credit
Teaching Language Türkçe
Level Belirsiz
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. ZEYNEL CEBECİ
Course Instructor
The current term course schedule has not been prepared yet.


Course Goal / Objective

This course aims to teach application development for deep learning in life sciences.

Course Content

This course covers the topics on application development for deep learning in life sciences.

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 Learns the machine learning concepts.
LO02 Learns the deep learning algorithms.
LO03 Learns programming and analysis with Julia.
LO04 Develops the deep learning applications for life sciences.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level


Week Plan

Week Topic Preparation Methods
1 Introduction to machine learning and deep learning Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
2 Introduction to deep learning in life sciences Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
3 Installation of Julia, Packages for Jula, Working with Julia Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
4 Data types and structures in Julia Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
5 Introduction to programming with Julia Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
6 Working with the package MLBase.jl Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
7 Working with the package JuliaML Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
8 Mid-Term Exam Preparation for the exam
9 Working with the package Scikitlearn.jl Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
10 Working with the package MachineLearning.jl Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
11 Working with the package Mocha.jl Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
12 Survey on deep learning in agriculture Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
13 Applying machine learning to agricultural data Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
14 Applying machine learning to agricultural data Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
15 Deep learning in precision agriculture Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic.
16 Term Exams Preparation for the exam
17 Term Exams Preparation for the exam

Update Time: 15.01.2019 02:04