This repository contains lectures, homeworks, labs, quizes and exams for the course.
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured[1]. This course introduces methods for four key aspects of data science:
- Data acquiring
- Data preprocessing
- Exploratory Data Analysis
- Data Modelling
This course is designed for graduates from various fields.
So, if you are a student in, for example, Computer Science, Electrical Engineering, Mechatronics, Telecom Engineering, Social Sciences, Business, etc., and want to learn some computational and quantitative skills to be successful in your field as it transforms in an age increasingly dominated by data and computation, this course might be for you!
This is an advanced course: we will introduce both programming concepts and the necessary mathematics.
We expect you to have background in python programming and math.
Their is no formal pre-requisite for the course because we are expecting a class of Graduate Engineers that are already acquainted with the right skills for the course.
ITU students can enroll for the course by contacting the academics office.
Faisal Kamiran
Director Data Science Lab, ITU
E-mail: [email protected]
Faizan Saeed
Umair Majeed
The class meets Tuesday, 05:30 PM-07:00 PM in LT-5 and Thursday, 07:15 PM-08:45 PM in Lab.
Lectures are used to introduce theoretical concepts.
Labs are used to teach coding skills and revisit the concepts introduced in lectures in practical terms. We will typically run coding exercises in the lab. Please bring your laptop computer!
Office Hours:
TA office hours: Tuesday and Thursday, 05:30-08:30 PM, Data Science Lab
Dr. Faisal office hours: Wednesday, 4:00 - 6:00 PM, Data Science Lab
Online discussion, submissions, grades, etc: We use Google Classroom for discussions and questions.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent