Python for Data Analytics Certified within 5 Weeks

         Course Overview

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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

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

Challenges that You will Overcome

• Gaps between Academics and Industry Requirements

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•  Lack of Professional Network and Working Experience in Data Analytics

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• Information Overloaded by Numerous Non-interactive Online Courses

Benefits

that You will Gain

• 5-week of intensive learning and systematic approach

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

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

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

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• Certificate will be provided by Coursera on Python learning

Curriculum Design Philosophy

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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.

         Eligibility ​

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

          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.
 

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Module 1 :

Python Basics

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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.

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Pre-Course Reading​

• Basic Python Semantics: Variables and Objects

• Basic Python Semantics: Operators

• Built-In Types: Simple Values

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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

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Assignment

• Quiz: Types

• Quiz: Expressions and Variables

• Quiz: String Operations

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          Course Outline

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Module 2 :

Python Data Structures

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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.

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Pre-Course Reading

• Built-in Data Structures

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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

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Assignment

• Quiz: Lists and Tuples

• Quiz: Sets

• Quiz: Dictionaries

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Module 3: Python Programming Fundamentals

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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.

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Pre-Course Reading

• Control Flow

• Defining and Using Functions

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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

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Assignment

• Quiz: Conditions and Branching

• Quiz: Loops

• Quiz: Functions

• Quiz: Objects and Classes

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Module 4 :

Working with

Data in Python

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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.

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Pre-Course Reading

• Modules and Packages

• A Preview of Data Science Tools

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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

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Assignment

• Quiz: Reading files with open

• Quiz: Writing files with open

• Quiz: Loading data with Pandas

• Quiz: NumPy

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Module 5:

Capstone Project

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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

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Course Preview