Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also look at some popular data visualization libraries in Python.
Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analysing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through several plotting systems in Python.

Additional Info

  • Certification Course only
  • Course Code Data Analysis using Python
  • Price 4000
  • Exam Price Exclude
  • Duration 1 Day
  • Schedule

    available upon request

  • Prerequisities

    Knowledge and experiences working with other programming languages is a bonus but are not necessarily required.

  • Module 1 Title Chapter 1: Data Gathering and Cleaning
  • Module 1 Content

    Cleaning data
    Reading and Cleaning CSV Data
    Merging and Integration Data
    Reading Data from the JSON Format
    Reading Data from HTML Format
    Reading Data from the XML Format

  • Module 2 Title Chapter 2: Data Exploring and Analysis
  • Module 2 Content

    Series Data Structures
    Data Frame Data Structures
    Data Analysis

  • Module 3 Title Chapter 3: Data Visualization
  • Module 3 Content

    Direct Plotting
    o Line Plot
    o Bar Plot
    o Pie Chart
    o Box Plot
    o Histogram Plot
    o Scatter Plot
    Seaborn Plotting System
    o Strip Plot
    o Box Plot
    o Swarm Plot
    o Joint Plot
    Matplotlib Plot
    o Line Plot
    o Bar Chart
    o Histogram Plot
    o Scatter Plot
    o Stack Plot
    o Pie Chart

  • Module 4 Title Chapter 4: Case Studies
  • Module 4 Content

    Case Study 1: Cause of Deaths in the United States (1999-2015)
    Case Study 2: Analysing Gun Deaths in the United States (2012-2014)

RM4,000.00(+RM240.00 Tax)
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PenjanaKerjaya 3.0 - Training Incentive

In addition to the Malaysian government's Short-Term Economic Recovery Plan, the government has launched a slew of initiatives to help businesses maintain and survive the pandemic financially. One of the efforts aimed at encouraging firms to create jobs is the Hiring Incentive Program (Penjana Kerjaya).

What is Penjaya Kerjaya 3.0

The Penjana Kerjaya 3.0 is an extension to the hiring incentives program 2.0 that has ended by 30 June 2021.

These hiring incentives program was enhanced with the aim to reduce unemployment among the local. Those eligible employers will be receiving 40% to 60% of the subsidy of total employee’s salary for 6 months.

Who Is Eligible To Apply For Penjanakerjaya 3.0 Hiring Incentive?

The application date for Penjana Kerjaya 3.0 started from 15 July 2021 onwards. The last day of application is on 31 December 2021.

  1. Employers from all industries registered with SOCSO except sole proprietorship employers: Employers registered with SSM before 1 January 2021 or other authorities such as ROS, ROB, Local Authorities etc
  2. Public sector employers, federal and state statutory bodies, statutory bodies with separate remuneration scheme, local authorities (PBT), are eligible for the apprenticeship category


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  • Employer’s bank account details (Front page displaying employer’s name, account bank, and bank’s name)
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  • Employee’s bank account details (Bank statement’s front page displaying employee’s name, account number, IC number and bank’s name)
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Employers can use this program to hire new personnel, as well as upskill or reskill their recently hired employees. Iverson Associates programs are recognized under Penjana Kerjaya 3.0 by providing list of Training course especially ease up your organization plan into business digital transformation especially network security, data analysis and many more provided by global well know service provider with Iverson Associates certified trainer.


Information Source:

Duration: 4 days


Course Objective

The objective of this course is to train Social Media Specialist and Community Manager to use video marketing as a sales tool, develop viable video marketing projects with clear KRAs and ROIs, and design marketing plan that aligns with business goals using 3MORE Framework.


1. Basic English literacy.

2. Poses mobile phone with video camera and internet connection.


Learning Outcome

At the end of this 32-hours session, participants will be able to:

1. Adopt 3MORE Framework for social media campaigns.

2. Design and produce video content with low budget and in short timeframe.

3. Use video to market and close sales.

4. Determine KRAs, KPIs, and ROI for video marketing project.


Learning Outline

1. Introduction to 3MORE Framework

a. Align social media strategies to business goals.

b. Brand value and market mapping.


2. Video marketing techniques and strategies

a. High performance low-cost video marketing techniques

b. Adopt agile video marketing strategies


3. Video marketing is a sale and a marketing tool

a. Video marketing in sales cycle

b. Automation in video marketing

c. Best practice and tools


4. Implement video marketing using 3MORE Framework

a. Key Result Areas (KRAs) for social media.

b. Return On Investment (ROI) in social media.


Pricing: Contact us for further information

Duration: 24 days


Course Objective

The objective of this course is to train Digital Marketing Executive fundamental of digital marketing and social media and to help them to develop strategies using customer journey mapping.



1. Basic English literacy.

2. Poses mobile phone with video camera and internet connection.


Learning Outcome

At the end of this 24 days session, participants will be able to:

1. Understand digital marketing and social media fundamentals and develop strategies, align result to business goals, and develop action plans.

2. Develop and deploy search engine related strategies including preparation and execution of daily activity plans.

3. Choose the right social media platform and align social media strategies to business goals.

4. Design omnichannel digital customer experiences and journeys.

5. Develop strategies to select, manage, and measure influencers.


Learning Outline

1. Digital Marketing Strategy &Planning

a. Understanding customer journey

b. Marketing functions and practical strategies

c. Set objectives, keywords research, and optimize keyword


2. Content Marketing

a. Concept, research, and content marketing plan

b. Content creation and content curation

c. Measure results and key indicators


3. Search Engine and Optimization

a. Search Engine Optimization (SEO)

b. Search Engine Results Page (SERP)

c. Search Engine Marketing (SEM)


4. Social Media Marketing

a. Facebook, Twitter, LinkedIn, Instagram, and TikTok

b. Community building and management

c. Paid campaign and advertisement


5. Digital Experience

a. Concept, architecture, and design

b. Optimization

c. Measurement and key indicators


6. Influencer Marketing

a. Influencers and Key Opinion Leaders (KOLs)

b. Choosing the right influencer and KOL

c. Influencer marketing goals and key results

d. Influencer management and ROI


Pricing: Contact us for further information

Duration:  8 days


Course Objective

The objective of this course is to train Community Manager to use social media as the foundation to engage with stakeholders for brand building, lead generation, sales, and customer service.



1. Basic English literacy.

2. Poses mobile phone with video camera and internet connection.


Learning Outcome

At the end of this 64-hours session, participants will be able to:

1. Develop balanced community building strategies that aligns to business goals and delivers positive impact to community.

2. Understand fundamental search algorithm in different social media platforms, e-commerce platforms and search engine.

3. Design community strategies using consumer behavior theories and Neuro-Linguistic Programming (NLP) techniques.

4. Adopt data analytics and business intelligence into social media and community management.

5. Assess business brand, sustainability, and ethics in social media marketing and activities.


Learning Outline

1. Introduction to business in digital-driven consumer market

a. Post-covid consumer market

b. Business landscape in digital driven world

c. Shift in consumerism


2. Social Media and Search Engine fundamental

a. Facebook, Instagram, TikTok, YouTube, and LinkedIn fundamental

b. Fundamental of search algorithm and result optimization for Shopee, Lazada, and Google


3. Consumer behaviour and community relationship

a. Fundamental of Neuro-Linguistic Programming (NLP) in consumer behaviour

b. Buyer behaviour and consumer behaviour fundamental

c. Human dynamics and relationship management

d. Business, consumer, and community mapping techniques


4. Visualization, intelligence, and technology

a. Visualization techniques and tool

b. Build omnichannel business intelligence

c. Ready tools and customization

d. Build real-time dynamic dashboard

e. Automated reporting for management and operation


5. Build a lasting business

a. Business brand and sustainability

b. Ethics in marketing for a better society


Pricing: Contact us for further information

DATE : 15/09/2021

Module Title:  Data Analysis and Statistic with Python

Duration: 2 Days 11 – 12 Oct 2021

What you'll learn

• Understanding the basic statistic and how you can use it for different machine learning scenarios

• Become Proficient In Using The Most Common Python Data Science Packages Including Numpy, Pandas, Scikit & Matplotlib

• Be Able To Read In Data From Different Sources (Including Webpage Data) & Clean The Data

• Carry Out Data Exploratory & Pre-processing Tasks Such As Tabulation, Pivoting & Data Summarizing In Python

• Become Proficient In Working With Real Life Data Collected From Different Sources

• Carry Out Data Visualization & Understand Which Techniques To Apply When

• Carry Out The Most Common Statistical Data Analysis Techniques In Python Including T-Tests & Linear Regression

• Understand The Difference Between Machine Learning & Statistical Data Analysis

• Implement Different Unsupervised Learning Techniques On Real Life Data

• Implement Supervised Learning (Both In The Form Of Classification & Regression) Techniques On Real Data


Who this course is for

• Anyone Who Wishes To Learn Practical Data Science Using Python

• People Looking To Work With Real Life Data In Python

• Anyone With A Prior Knowledge Of Python Looking To Branch Out Into Data Analysis

• Anyone Looking To Become Proficient In Exploratory Data Analysis, Statistical Modelling & Visualizations Using iPython



Course Outline

1- Introduction to the Data Science in Python

• What is Data Science?

• Introduction to the Python Data Science Tool

• Introduction to the Python Data Science Environment


2- Introduction to Python Pre-Requisites for Data Science

• Different Types of Data Used in Statistical & ML Analysis

• Different Types of Data Used Programatically

• Python Data Science Packages To Be Used


3- Introduction to Numpy

• Numpy: Introduction

• Create Numpy Arrays

• Numpy Operations

• Matrix Arithmetic and Linear Systems

• Numpy for Basic Vector Arithmetric

• Numpy for Basic Matrix Arithmetic

• Broadcasting with Numpy

• Solve Equations with Numpy

• Numpy for Statistical Operation


4- Introduction to Pandas

• Data Structures in Python

• Read in Data

• Read in CSV Data Using Pandas

• Read in Excel Data Using Pandas


5- Data Pre-Processing/Wrangling

• Removing NAs/No Values From Our Data

• Basic Data Handling: Starting with Conditional Data Selection

• Drop Column/Row

• Subset and Index Data

• Basic Data Grouping Based on Qualitative Attributes

• Crosstabulation

• Reshaping

• Pivoting

• Rank and Sort Data

• Concatenate

• Merging and Joining Data Frames


6- Introduction to Data Visualizations

• What is Data Visualization?

• Some Theoretical Principles Behind Data Visualization

• Histograms-Visualize the Distribution of Continuous Numerical Variables

• Boxplots-Visualize the Distribution of Continuous Numerical Variables

• Scatter Plot-Visualize the Relationship Between 2 Continuous Variables

• Barplot

• Pie Chart

• Line Chart


7- Statistical Data Analysis-Basic

• What is Statistical Data Analysis?

• Some Pointers on Collecting Data for Statistical Studies

• Some Pointers on Exploring Quantitative Data

• Explore the Quantitative Data: Descriptive Statistics

• Grouping & Summarizing Data by Categories

• Visualize Descriptive Statistics-Boxplots

• Common Terms Relating to Descriptive Statistics

• Data Distribution- Normal Distribution

• Check for Normal Distribution

• Standard Normal Distribution and Z-scores

• Confidence Interval-Theory

• Confidence Interval-Calculation


8- Statistical Inference & Relationship Between Variables

• What is Hypothesis Testing?

• Test the Difference Between Two Groups

• Test the Difference Between More Than Two Groups

• Explore the Relationship Between Two Quantitative Variables

• Correlation Analysis

• Linear Regression-Theory

• Linear Regression-Implementation in Python

• Conditions of Linear Regression

• Conditions of Linear Regression-Check in Python

• Polynomial Regression

• GLM: Generalized Linear Model

• Logistic Regression

This course is the most comprehensive review of information security concepts and industry best practices, and covers the eight domains of the official CISSP CBK (Common Body of Knowledge). You will gain knowledge in information security that will increase your ability to successfully implement and manage security programs in any organization or government entity. You will learn how to determine who or what may have altered data or system information, potentially affecting the integrity of those asset and match an entity, such as a person or a computer system, with the actions that entity takes against valuable assets, allowing organizations to have a better understanding of the state of their security posture. Policies, concepts, principles, structures, and standards used to establish criteria for the protection of information assets are also covered in this course.

This five-day program is comprised of a total of eight domains and includes:

  • Official (ISC)2 Guide to the CISSP Common Body of Knowledge® (CBK) (electronic format)
  • Official (ISC)2 CISSP Training Handbook
  • Official (ISC)2 CISSP Flash Cards
  • CISSP Certification Exam Voucher


Audience Profile

  • Anyone whose position requires CISSP certification
  • Individuals who want to advance within their current computer security careers or migrate to a related career



Professionals with at least five years of experience and who demonstrate a globally recognized level of competence, as defined in the CISSP Common Body of Knowledge (CBK) in two or more of the eight security domains


At Course Completion

In-depth coverage of the eight domains required to pass the CISSP exam:
1. Security and Risk Management
2. Asset Security
3. Security Engineering
4. Communications and Network Security
5. Identity and Access Management
6. Security Assessment and Testing
7. Security Operations
8. Software Development Security


Course Outline

Module 1: Security and Risk Management (e.g., Security, Risk, Compliance, Law, Regulations, Business Continuity)

Module 2: Asset Security (Protecting Security of Assets)

Module 3: Security Engineering (Engineering and Management of Security)

Module 4: Communications and Network Security (Designing and Protecting Network Security)

Module 5: Identity and Access Management (Controlling Access and Managing Identity)

Module 6: Security Assessment and Testing (Designing, Performing, and Analyzing Security Testing)

Module 7: Security Operations (e.g., Foundational Concepts, Investigations, Incident Management, Disaster Recovery)

Module 8: Software Development Security (Understanding, Applying, and Enforcing Software Security)

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