Japan-based Online International Education Platform

Organisational Data Science Course

Cambridge Online Programme
・ One-to-One lesson
・ Group lesson (5 students at minimum)


Simultaneous bidirectional type Online by ZOOM

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Subject field
Data science, Education, Language, International affairs, Humanities & Social sciences, Business & Management, Qualifications & Examinations
Course coordinator
Masumi Akaishi
Target
General
Consultants
Mid-level to senior HR professionals
Project managers
Directors and functional heads
Employee representatives 
大学生 University students
Fee: 300 GBP
提供
ICC International Communications Councilロゴ;
Lecture
1 lecture
Video
video
Required time
A month
Language
Japanese, English
Subtitles
Japanese, English
Required Japanese language level
None
Purpose
Take a course, Career up
Issue
Certificate
Start month
Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec
Open period
~
Contents
Lecturers
Competencies
Other information
Contact

Course

course_image
    • Last update
    • 2022-06-29
    • Start month
    • Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec
    • Required time
    • A month
    • Lecture time
    • 60min more
    • Open period
    • ~
    • Delivery method
    • Live
    • Course restrictions
    • FCFS
    • System requirements
    • PC
Keywords
Online, 1:1Lesson, Recurrent Education, Data science, Simultaneous bidirectional Online, ZOOM, Group Lesson, One-to-One lesson

Contents

1
Simultaneous bidirectional type Online by ZOOM
Course
Organisational Data Science Course
Organisational Data Science Course Online Programme・ One-to-One lesson・ Group lesson (5 students at minimum)
Simultaneous bidirectional type Online by ZOOM
Course
Organisational Data Science Course

Lecturers

Course coordinator

Programme Director
Asia Programme
ICC International Communications Council
  • The Embassy of Japan, Washington, D.C., USA  The Protocol
  • University of Oxford, Lecturer
  • University of Cambridge, Lecturer
  • University of London, SOAS, Lecturer
  • University of British Columbia, Lecturer
  • ICC International Communications Council, Programme Director

Competencies

Logical thinking ability, Problem finding ability, Problem solving skill, Creativity, Practical ability, Situation grasping ability, Communication ability, Management ability, Leadership ability, International character, Autonomy

Course requirements

Organisational Data Science Course

     ・One-to-One Simultaneous bidirectional type Online by ZOOM

750GBP(Deposit 100GBP is included)/ 1 person

     ・Group (5 students at minimum) Simultaneous bidirectional type Online by ZOOM

300GBP(Deposit 100GBP is included)/ 1 person

Fees and Dates 2022 – Organisational Data Science Courses Click here.

Apply:http://icc-edu.com/entryform_en/form.php

Required English proficiency:IELTS 6.0 / TOEFL iBT 80- /  CEFR B2 equivalent

English Proficiency Conversion

 

Syllabus

Essential Math and Statistics

The basic mathematical knowledge required for data science, focusing on probability theory (including conditional probability, mutually exclusivity, and Bayes’ theorem), distributions (including normal distributions and central limit theorems, binomial distributions, and alternative distribution models), and variables (including mean, variance, and standard deviation).

 

Essential Coding

A summary of the various coding languages, and a look into how to program key functions and variables in Python, including lists, tuples, dictionaries, and Boolean and conditional variables.

 

Predictive Analytics: Linear Modeling

How we can use linear algebra to make predictions about the behavior of a complex system, or analyse data sets. Looking at linear regression, multiple linear regression (MLR), and logistic regression.

 

Predictive Analytics: Machine Learning

How we can use artificial intelligence (AI) to predict increasingly more accurate results using historical data, without specifically programming more for accurate results. Includes looking at the differences between supervised and unsupervised learning, and the various methods of machine learning, such as clustering (random forest, SVM, and k-means), dimensionality reduction, transfer learning, reinforcement learning, neural nets and deep learning, and natural language processing.

 

Visualizing Data and Exploratory Analysis

How we display data, and how to use a data visualization package, using real data to map trends in real life scenarios. A deep dive into how both data and analysis can be affected by biases and systematic errors, and how these can greatly affect visualizations.

 

Data Mining

Learning the principles of data mining – or how we process large data sets to extract trends and patterns. Looking at how these patterns obtained can be used in business intelligence and real time analytics. Looking at how data mining techniques can be integrated with machine learning.

 

Data Warehousing 

Understanding the various tiers of data warehousing, and how it can be used as a central hub for information.  How it differs from databases and data lakes, and when each of these data storage structures would be appropriate.

 

Big Data

Understanding how we collate and analyze the more complex data sets of big data, both structured and unstructured. Introduction to tools such as Hadoop, Spark, and Flink.

 

Data Storytelling

How to weave data and analytics into text, or how to present data in a way that tells an accurate story of what is occurring. Learning how to utilize the techniques taught in previous sessions to collect specific data to understand a concept, and how to relay that to other people without expertise.

 

Cloud Computing   

How cloud computing has started to dominate the fields of managing, storing, distributing and processing data. Learning Cloud platforms such as AWS and Microsoft Azure, and core concepts such as IaaS (Infrastructure as Service), PaaS (Platform as Service), and SaaS (Software as Service).

 

Evaluation method

Presentation

Attendance to the course

References

Organisational Data Science Online Course

The tutors have degrees from Cambridge University Judge Business School, Oxford University, or London School of Economics and they are all excellently qualified to teach Data Science.

Cambridge Data Science Course is a course to learn about topics such as Big Data, Data Mining, Crypto Currencies, Data Visualization, GDPR, Digital Encryption, and Artificial Intelligence to drive logical decision-making, with the support of the University of Cambridge Mathematics Faculty and Cambridge Judge Business School.

Data Science has grown rapidly in importance and plays a pivotal role in helping organisations leverage data, turning raw information into actionable insights.  It is an interdisciplinary field, using both statistics and computer sciences, to help solve some of the world’s most serious problems.

Let us take an example from the picture of Rabbit-duck illusion below.

One and the same picture can be a rabbit or a duck, depending on how it is construed.

Here, an objective analysis is required in order to prove that it is a rabbit or that it is a duck.  It is not convincing or persuasive just to say that it ‘looks like’ a rabbit or a duck.

Data analysis and statistics have become a focal point of public attention, with their broad range of use cases across industries and applications, from commercial, retail, legal, medical and even political fields.  Data Science has become an inevitable pillar within many organisations, including those of the giants, such as Google, Facebook, Microsoft and Amazon.

Special notes

Applyhttp://icc-edu.com/entryform_en/form.php

・For one-to-one lesson course, tuition fee is  750GBP (Deposit 100GBP is included) per student.

・For a group (5 students at minimum) lesson course, tuition fee is  300GBP (Deposit 100GBP is included) per student.

・Required English proficiency:IELTS 6.0 / TOEFL iBT 80- /  CEFR B2 Equivalent(No need to submit your score.)

English Proficiency Conversion

・On the Certificate of Attendance, name of the student, name of the course, dates of the course, lesson hours, and the grades are written.

・The teacher will start the lesson and finish the lesson on time.

・The student won’t have a make-up lesson if he/she gets late for the lesson or were absent from the lesson.

・Prepare your PC has a good internet access.

・Make sure you attend the lesson in a quiet environment.

・More than 1 course will be delivered at the same time on the same dates.  The student won’t be able to change the course once his/her course has started.

Contact

icccontact@internationalcommunicationscouncil.com

japanoffice@internationalcommunicationscouncil.com