Unprecedented explosion of data is impacting many areas of business, science, engineering, and industry. From analysing market trend to modelling traffic patterns of online customers, the enormous data is creating new opportunities and challenges in many areas of our environment.
To handle these challenges, the analyst must be trained to store, clean, manage, process and analyse data. Python is one of the most important and popular programming language in data analytics to perform these tasks supported by vasPt libraries, tools and support communities.
The main goal of this course is to help participants learn, understand and practices data analytics and basic machine learning approaches using Python Programming Language, including basic Python syntax, importing of data, data cleaning, data wrangling and basic applications of machine learning.
[III] WHO SHOULD ATTEND
• Data Analyst
• Market Analyst
• Software Developer
• IT Engineer
• IT Project Manager
• To demonstrate an understanding of knowledge and skills in the area of data analytics
• To be able to code in Python
• To be able to work in Python data analytics environment – Anaconda, Jupyter Notebook & IDE
• To be able to perform data massaging, analytics and visualisation using Python’s Pandas, Numpy & Matplotlib
• To demonstrate an understanding of knowledge and application in basic Machine Learning models (using Scikit-Learn)
[V] DATE, TIME & FEE
DATE: 23 - 25 February 2021 (Tue - Thu)
TIME: 9am - 5pm
MODE: Online/ Interactive
- Early Bird Offer (before 6 Feb 2021) - RM1200
- Special Offer (before 20 Feb 2021) - RM1300
- Fee - RM 1400
>> Fee includes Course Notes, Certificate of Attendance & 6% Government Service Tax
(i) SST2u Learner Card Member - overriding 15%
[VI] COURSE OUTLINE
MODULE 1: Introduction To IR4.0 and data revolution
• An introduction to Industry 4.0
• Current and Future data revolution
MODULE 2: Introduction to Data Analytics
• What is Data Science & Data Analysis?
• Application and use cases of machine learning
• Exploratory data analysis
• Correlation Coefficient
• Introduction to Python Data Analytics modules
MODULE 3: Introduction to Python Programming I
• Data Types
• Conditional Flow
MODULE 4: Introduction to Python Programming II
• Python Class & Object Oriented
• Python Modules
MODULE 5: Introduction to NUMPY
• Numpy Array
• Data Types
• Basic Functions in Numpy
• Designing a real-world database
• Normalizing a table
MODULE 6: Introduction to PANDAS
• Pandas Dataframes and Series
• Importing data to Pandas
• Exploring Data Frame
• Data Frame Data Types
• Data Frame Filtering & Slicing
MODULE 7: Introduction to Matplotlib
• Plotting with Matplotlib
• Parameters and usage guides.
MODULE 8: Handling Missing Values
• Methods to deal with missing values
• Dropna and fillna
• Forward fill and backward fill
• Replacing unrecognized value
MODULE 9: Introduction to Machine Learning
• Unsupervised vs Supervised Learning
• Regression vs classification
• Linear Regression
• Multivariate linear regression
• K-means clustering
• Decision Tree and Random Forest Classification
Recap & Review of basic data analytics
[VII] SPEAKER PROFILE
TAN SU TUNG
Python Data Analytics Trainer
Certified HRDF Trainer
ST Tan has been deeply involved in dala analytics
primarily in the areas of:
• Creation of Virtual Human Anatomical models via CT & MRI DICOM data.
• Big Data Implementation in Operating Theater solutions.
• Design and fabrication of customized implants for cranioplasty surgery.
• Design and fabrication of surgical human anatomical Biomodels for surgical training.
• Design of Biomodels using CT & MRI image fusion.
• Design of Digital Operating Theater software solutions.
• Linux based software architecture, design & development.
• Web based application development and Real Time Communications.
He holds a Master in Science in Information Technology from Malaysia University of Science and Technology. He is currently the Chief Technical Officer of a university-owned subsidiary specializing in areas of data analysis.
His research works have been published extensively including in the areas biomedical engineering, neuro navigation, 3D rapid prototyping and image processing. His current research has generated successes in the areas of Search Engine Spam/ Link Spam after successfully manipulating search engines’ ranking algorithm including HITS (Hypertext Induced Topic Distillation) and Google’s PageRank using Tightly-Knit Community (TKC) effect.
As a Python Data Analytics Trainer, he has successfully trained professionals, lecturers, trainers, students from both the Commercial and Academic sectors, including one of the largest banks in Malaysia.
[VIII] ENQUIRY & REGISTRATION
- General (03 - 8082 3357)
- Teo (011 - 3178 9203)
- Logesh (012 - 503 0346)
- Siti (012 - 383 8603)
- Han (019 - 323 0507)