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         Course Overview

The accelerated course has adopted the innovative education concept of “Flipped Classroom” - a subject matter expert (BestTop’s mentor) in data analytic will be there to guide beginners throughout the course. With structured curriculum and interactive online session via Zoom, the accelerated course aims to provide you with the essential knowledge of Python in data analytics field and also its practical applications.

 

Apart from the technical training on Python, BestTop invited 4 working professionals from leading technology firms, including Google, Amazon, Shopee, and Grab, to share their knowledge of industrial trend and interview preparation tips. Upon completing all sessions and its demanding assignments, you will get an official certificate on Python from the leading Massive Open Online Courses (MOOC) platform – Coursera.

Innovative Education:  Pre-course Study + Interactive in-class Discussion

Overcoming Laziness::   Critical Thinking + Attentive Q&A Sessions

Flipping Classroom

 “Flipped Classroom” is an emerging method of education. Participants are required to teach themselves the course materials before the classroom session, and then they discuss with the teachers interactively during the classroom session to solve their questions and problems.

 

Widely used by Khan Academy and MOOC, “Flipped Classroom” is able to deepen the learning results because it prompts its participants to think more independently and more thoroughly.

Challenges that You will Overcome

 

  • Gaps between Academics and Industry Requirements

  •  Lack of Professional Network and Working Experience in Data Analytics

  • Information Overloaded by Numerous Non-interactive Online Courses

Benefits

that You will Gain

 

  • 5-week of intensive learning and systematic approach

  • Attentive guidance from data sciences with 8 years of relevant experience

  • Unique sharing sessions with 4 working professionals in data analytics field

  • A study group will be formed for participants to support one another

  • Certificate will be provided by Coursera on Python learning

Curriculum Design Philosophy

BestTalent online course are co-developed by BestTop and career mentors with abundant industry knowledge. It follows the “RICE” coaching methodology, with the goal centralizing on career development. Participants will gain comprehensive technical knowledge within a short period of time, while completing the career preparation in a specific industry.

Real-time Interaction

Live session in small group setting to address specific questions

Incremental Learning

 Learning is divided into incremental stages, from zero to hero

Career-driven Goal

 Only practical knowledge is passed on to deal with real-life situations

Experienced Mentor

Sessions are delivered by experienced practitioners from leading firms

         Eligibility 

Anyone with an opened mind to get their hands dirty in data analytics! All is welcome!

Course

Mentor

Guest

Speakers

-    SMU Msc. in Applied Finance 应用金融
-    8-year working experience in Data Science 8年数据分析实践工作经验
-    Worked at Deutsche Bank, KPMG, Uber, Grab, Ant Financial 曾任职于

Mentor A is a cross-disciplinary data professional with more than eight years of experience working in a diverse range of domain areas including Tech, Investment Banking, and Wealth Management; leveraging his knowledge in Machine Learning, Deep Learning, CRM Analytics, Investment Analytics, Business Intelligence, Financial Modelling, Company Valuation, and Portfolio Management.

4 guest speakers from leading firms, including Google, Amazon, Shopee and Grab, will come along to share topics such as,

  • Day-to-day jobs carried out by data analyst/scientist in Singapore

  • Career advice for analytics and data science field

  • Industry trend and development of data analytics field in Singapore

          Course Agenda

This course contains of 5 sessions, with Session 1 lasting for 2 hours and the rest sessions lasting for 2.5 hours. Participants are required to pre-study relevant online course materials before Session 2 ~ 5, and mentor will deliver live lecture and address questions afterwards.

After each session, assignment will be given to evaluate learning progress of participants. Other than that, exclusive WhatsApp group is created, and teaching assistant will address participants’ questions as much as possible between the sessions.
 

Session 1: 29th Feb (Saturday)

9:30am – 11:30am

Session 2: 07th March (Saturday) - Guest Speaker #1

9:30am – 12:00noon 

Session 3: 14th March (Saturday) - Guest Speaker #2

9:30am – 12:00noon

Session 4: 21st March (Saturday) - Guest Speaker #3

9:30am – 12:00noon

Session 5: 28th March (Saturday) - Guest Speaker #4

9:30am – 12:00noon

Module 1 :

Python Basics

Objective

  • Interpret variables and solve expressions by applying mathematical operations.

  • Describe how to manipulate strings by using a variety of methods and operations.

  • Demonstrate an understanding of types in python by converting/casting data types: strings, floats, integers.

Pre-Course Reading

  • Basic Python Semantics: Variables and Objects

  • Basic Python Semantics: Operators

  • Built-In Types: Simple Values

Course

  • Video: Types

  • Video: Expressions and Variables

  • Video: String Operations

  • Jupyter Notebook Interactive Learning:  Your First Program, Types, Expressions & Variables

  • Jupyter Notebook Interactive Learning:  Strings

Assignment

  • Quiz: Types

  • Quiz: Expressions and Variables

  • Quiz: String Operations

          Course Outline

Module 2 :

Python Data Structures

Objective

  • Understand tuples and lists by describing and manipulating tuple combinations and list data structures.

  • Demonstrate understanding of dictionaries by writing structures with correct keys and values.

  • Understand the differences between sets, tuples, and lists by creating sets.

Pre-Course Reading

  • Built-in Data Structures

Course

  • Video: Lists and Tuples

  • Video: Sets

  • Video: Dictionaries

  • Jupyter Notebook Interactive Learning:  Lists and Tuples

  • Jupyter Notebook Interactive Learning:  Sets

  • Jupyter Notebook Interactive Learning:  Dictionaries

Assignment

  • Quiz: Lists and Tuples

  • Quiz: Sets

  • Quiz: Dictionaries

Module 3: Python Programming Fundamentals

Objective

  • Understand loops by using visual examples and comparing them to tuples and lists.

  • Understand functions by building a function using inputs and outputs.

  • Explain objects and classes by identifying data types and creating a class.

  • Classify conditions and branching by identifying structured scenarios with outputs.

Pre-Course Reading

  • Control Flow

  • Defining and Using Functions

Course

  • Video: Conditions and Branching

  • Video: Loops

  • Video: Functions

  • Video: Objects and Classes

  • Jupyter Notebook Interactive Learning: Conditions and Branching

  • Jupyter Notebook Interactive Learning: Loops

  • Jupyter Notebook Interactive Learning: Functions

  • Jupyter Notebook Interactive Learning: Objects and Classes

Assignment

  • Quiz: Conditions and Branching

  • Quiz: Loops

  • Quiz: Functions

  • Quiz: Objects and Classes

Module 4 :

Working with

Data in Python

Objective

  • Understand how to use pandas for library and data analysis by using commands.

  • Demonstrate how to create a text file by using the open function.

  • Demonstrate an open function to create and identify a file object.

  • Demonstrate how to use NumPy to create multi-dimensional arrays.

Pre-Course Reading

  • Modules and Packages

  • A Preview of Data Science Tools

Course

  • Video: Reading files with open

  • Video: Writing files with open

  • Video: Loading data with Pandas

  • Video: NumPy

  • Jupyter Notebook Interactive Learning: Reading files with open

  • Jupyter Notebook Interactive Learning: Writing files with open

  • Jupyter Notebook Interactive Learning: Loading data with Pandas

  • Jupyter Notebook Interactive Learning: NumPy

Assignment

  • Quiz: Reading files with open

  • Quiz: Writing files with open

  • Quiz: Loading data with Pandas

  • Quiz: NumPy

Module 5:

Capstone Project

Objective

  • Setup IBM Watson Studio environment

  • Analyzing US Economic Data and Building a Dashboard: Create a dashboard that shows key economic indicators from a specific data set

  • Peer Review

Course Preview

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