数据科学涵盖了数据分析,数据挖掘,统计预测及算法语言,是未来成为具有高薪的数据科学家,数据
数据科学课程较深奥,知识面广,是大学里新兴的专业课程,很多学生在进入大学后都觉得其学习难度大,是极不容易通过的课程。
现在我们推出简易版的数据科学暑期课程,主要着眼于基础概念,基本原理及简易课题训练,帮助立志于未来想申请计算机科学,软件工程, 统计等与数据有关的专业的高中学生打好一个未来学习的基础,减轻未来的学习难度,提高他(她)专业考试的通过率,同时也使他们未来找工作时能更加从容地面对面试人员。
本暑期课程对参加学生的要求如下:
1,9年级以上学生
2,加拿大本地学生和留学生均可
学生可报读以下任一或几种数据科学课程:
Course 1. Data analytics(数据分析,30 hrs)
Unit 1: Introduction of data analysis and its application
Unit 2: Organizing and cleaning data for projective purposes
Unit 3: Exploratory data with numerical methods
Unit 4: Data description using graphic methods
Unit5: Data binning and variable selection
Course 2. Statistical analysis (统计分析, 30 hrs)
Unit 1: Basic concepts of statistics
Unit 2: Definition of probability and probability distributions
Unit 3: Sample distributions and parameter estimation
Unit 4: Statistical hypotheses test
Unit 5: Correlation and simple regression
Course 3. Data mining(数据挖掘, 20 hrs)
Unit 1: Introduction of predictive analytics
Unit 2: Data exploring and mining
Unit 3: Linear Regression
Unit 4: Logistic Regression
Unit 5: Segmentation
Course 4. Predictive modelling(预测模型设计) (20 hrs)
Unit 1: Market basket analysis
Unit 2: Decision Tree
Unit 3: Time series analysis
Unit 4: Classification
Course 5. R language (R 算法语言, 20 hrs)
Unit 1: Install environment with windows and basic operation with R
Unit 2: Data structures
Unit 3: Functions
Unit 4: Loop and flow control
Unit 5: File I/O
Course 6. Python with Numpy (Python 算法语言) (20 hrs)
Unit 1: Python basics with IDE spyder
Unit 2: Data structures and operation
Unit 3: Loop and flow control
Unit 4: Python package Numpy
以上课程由加拿大数理博士授课,讲课语言:英文,辅导语言:中英文
上课地点:Highway 7 / Leslie st, Richmond Hill, ON
课程收费:$25/hr
联系电话:905-597-1490
E-mail: inf@newaurora.ca
开课日期:6月下旬
主办:多伦多大数据厨房
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