Apply before 21 July 2022 and avail early bird tuition assistance of RM 500.
What will you get out from this Training Program?
- Programming Analytics
- Python Functions
- Python Packages
- Data Manipulation
- Descriptive Analytics
- Predictive Analytics
This is a complete course that provides you detailed understanding of data science, encompasses basic statistical concepts to advanced analytics and predictive modeling techniques, along with data acquisition, analysis, statistical methods and machine learning. The objective of the course is to learn statistical analysis techniques and tool to solve business problems that help you to emerge as ‘Industry Ready’ professional in the field of Data Science. You will be learning the Data Science skills using Python and its numerical, machine learning, and NLP libraries, the most popular and leading programming language, analytical tools and libraries widely used across industries.
The training is divided into multiple modules that would you to explore the basics of the Python programming language, and once you become comfortable with the basics, we will gradually introduce the step-by-steps the features of the Python analytics libraries.
- Introduction to Programming and Business Analytics
- Coding Style and Kaggle Notebook
- Objects, Variables and Assignment Statements
- Data Types and Data Type Conversion
- Conditional Statements
- Iterations and Loops
- Introduction to Packages
- Datasets and Types of Variables
- Constructing, Indexing, and Slicing a pandas.DataFrame
- Accessing Columns and Rows in a pandas.DataFrame
- Working with Subsets
- Filtering Data
- Visualisation Techniques
- Relationship between Variables
- Time Trends
- Numerical Summaries
- Data Manipulation Using Pandas
- Data Visualisation Using Packages
- Normality Tests
- Correlation Tests
- Stationary Tests
- Parametric Statistical Hypothesis Tests
- Nonparametric Hypothesis Tests
- Distribution Types
- Probability Mass Functions (PMFs)
- Cumulative Distribution Functions (CDFs)
- Probability Density Functions (PDFs)
- Distribution Data Fitting
Dr. Amril currently works as the Chief Architect at a leading telecom analytics solutions provider. He has 15 years of experience in managing Artificial Intelligence and Big Data related projects from both academic and industry.
As the Chief Architect, he has led and managed USD$150M+ data science & big data technical project delivery and operational teams for the Company’s Telecommunication Traffic Monitoring and Tax Revenue Assurance system, which processes 20+ billion of CDR (Call Detail Records) transactions with an average of 4 Terabytes of binary and text data on a daily basis from telecommunication operators in India, Ghana, Guinea, and Sierra Leon.
He has conducted extensive data science training classes to students for the last 5 years in the Middle East. He earned his PhD in Computer Science from the University College London (UCL), UK.
Lujaini currently works as Lead Solution Analyst. He has vast experience implementing various Machine Learning algorithms using PyTorch, Sci-kit Learn, Tensorflow, YOLO and Darts.
In his previous work, he worked on various data analytics projects such as the Malaysian political sentiment analysis, image processing analysis, and exploratory covid-19 analysis. Currently, he is working on speech-to-text data modelling project.