Courses
Certified Python Programmer for Data Science (CPPDS)
Are you planning to become a data scientist? If yes, then you have to learn Python programming language. Why? Python is the number one programming language in the world of data scientists. It emphasises on code readability and clear programming on both small and large scales, allowing you to focus on your research, product, or project.
In this 4-day journey, you will be exposed to multiple development environments so you can choose the best one for you. You will be taught step-by-step how to program in Python. You will go through all the steps of a Data Science project starting from data importing, data cleaning, data analysing, to data visualisation which reveals new insights.
In summary, you will gain a complete understanding of Python with Data Science from the ground up.
Pass the 2-hour exam consisting of 50 Online Multiple Choice Questions with the score of 70% to earn this certification
One of the most industry validated digital skills certification in Asia. Course and exams is taken by the industries / academia / governments from 26 countries in Asia via 30+ Authorised Training Partners (ATP) and 50+ Authorised Academy Partners (AAP).
“Vendor-neutral” certifications refer to any certifications that are not directly associated with specific IT vendors. These certifications tend to develop a knowledge and skill base that is universally applicable and individual with skills that are more conceptual, setting you up to work with a greater range of products / tools.
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Do you yearn to pursue a career in data science someday? If yes, then a valuable Python certification is a sturdy weapon in the race for better employment, first-rate expertise and a greater competitiveness. This can open doors to better jobs and a better salary.
Python is a versatile language used by data scientists for various data science projects and applications. It emphasises on code readability and provides great functionality to deal with mathematics, statistics and scientific functions.
In this 5-days Python for Data Science journey, you will gain the ability to apply Python fundamentals to drive business solutions across industries.
This beginner-friendly course will guide you on the end-to-end process of data importing, data cleaning, data analysing, and data visualisation for new insights on your company’s data.
1- Familiarity with terms “Data Science” and “Machine Learning”.
2- Understanding of the basics of Python and write codes swiftly
3- Deal easily with file systems and different sources of data
4- Learn how to analyse, retrieve and clean data with Python
5- Make inferences and strong predictions using Data
- Recognize the meaning of the terms “Data Science” and “Machine Learning”.
- Understand the basics of Phyton.
- Develop and write code easily in Phyton.
- Deal easily with files and file systems.
- Deal with different sources of data.
- Analyse and visualise data to gain new insights.
Training Module
Introduction to Programming
- What is an Algorithm?
- What is Programming?
- The Natural Language of the Computer
- Machine Language
- Programming Language Levels
- Translators
Python Basics
- Identifiers, Lists, and Tuples
- Dictionaries, Sets and Strings
- Operators, Control Structures and Loops
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Jupyter Notebook
- Installing and Running Jupyter
- User Interface
- Checkpoints
Functions
- Functions
- Lambda and Map Functions
- Globals and Locals
Pythonic Programming
- List Comprehension
- Generator Expressions
- Exceptions Handling
Modules and Packages
- Modules
- Documentation
- Packages and Namespaces
Working with Files
- Create, Read, Update, Delete (CRUD) a File
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Object-Oriented Programming
- OOP in General
- Classes
- Objects
- Constructors
- Instance/Class Data
- Instance/Class Method
- Inheritance
OS Module
- Working with File Systems
- Walking Directory Trees
- Paths
- Filenames
- Directories
Working with Files
- Creating a File
- Reading a File
- Updating a File
- Deleting a File
Working with JSON Data
- What is JSON and Why Is It Important?
- Module, Serialisation and Deserialisation
Web Scraping (BeautifulSoup)
- What is Web Scraping
- HTML Tags
- BeautifulSoup Module
- Webpage Scraping Phase
Introduction to Matrix Processing (NumPy)
- What is NumPy?
- Ndarray Object, Data Types
- Array Attributes, Array Creation Routines
- Indexing and Slicing
- Array Manipulation
- Mathematical Functions
Data Analysis (Pandas)
- What is Pandas?
- Series
- Dataframes
- Data Importing
- Data re-processing
- Data Grouping
Data Visualization (Matplotlib)
- What is Matplotlib?
- Line Graphs
- Bar Graphs
- Pie Charts
- Histograms
- Scatter Plots
- Graph Attributes
- Text Annotation
Introduction to Applied Machine Learning (Scikit-learn)
- What is Machine Learning?
- Machine Learning Algorithm Types
- Main Steps in Machine Learning Projects
- Introduction to Scikit-learn Module
Capstone Project
Final Evaluation (Exam)
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