ADAV-DO: Advanced Data Analytics And Visualization

Name: ADAV-DO: Advanced Data Analytics And Visualization
Brand: Data Analytics
Price: 2500 MYR
Availability: InStock

RM 2,500.00

Advanced Data Analytics And Visualization – Turn Raw Data Into Business Intelligence That Drives Results

In today’s data-driven economy, insights aren't optional—they're a competitive edge. The Advanced Data Analytics And Visualization course is a practical, beginner-friendly 2-day program that teaches professionals how to confidently work with data, uncover insights, and communicate them with impact—even without a technical background.

Through hands-on exercises and real-world case studies, you’ll learn to:

Understand the data analytics lifecycle, from sourcing to interpretation
Apply descriptive statistics and identify patterns that drive better decisions
Build effective dashboards and data visualizations that speak to both technical and non-technical audiences
Explore the basics of predictive analytics and machine learning concepts to forecast trends
Communicate data stories that influence stakeholders and solve business problems

More than 90% of organizations say data is key to their strategy—yet fewer than 30% feel confident in their team's ability to interpret it. This course helps bridge that gap by empowering staff at all levels to think and act analytically.

Whether you're an executive, analyst, or student, this course builds your data confidence from the ground up—so you can contribute meaningfully to projects, reports, and strategic decisions.

No coding. No jargon. Just practical skills to make data work for you.

Training Duration: 2 Days

Certificate Of Completion Available
Group Private Class
VILT Class Available
SBL-Khas Claimable

Download Course Outline

To provide participants with a foundational understanding of data analytics principles, visualization techniques, and their application in addressing business challenges. This course aims to demystify key concepts and equip participants with the knowledge to engage confidently in data-related discussions and projects.

What you will learn:

The fundamentals of what data analytics is and why it matters.

How to think about data: types, sources, and quality considerations.

An overview of the process used to analyse data, from collection to interpretation.

Basic statistical ideas to help make sense of data patterns (like averages and trends).

How to choose the right charts and graphs to represent data effectively.

The role of dashboards in monitoring performance and integrating data.

An introduction to the concepts of forecasting future trends using data (predictive analytics & machine learning).

Strategies for presenting data stories and insights clearly and concisely.

How to connect data analysis techniques to real-world business questions.
Upon successful completion of this course, participants should
be able to:

Define data analytics and explain its importance in various contexts.

Identify different types of data and common data sources.

Describe the basic steps involved in the data analysis process.

Understand fundamental statistical concepts used in data interpretation.

Recognise the principles of effective data visualization.

Explain the purpose and components of dashboards and Key Performance Indicators (KPIs).

Grasp the basic concepts behind predictive analytics and machine learning.

Understand the importance of communicating analytical findings clearly, especially to non-technical audiences.

Identify ways data-driven approaches can help solve business problems.
Day 1: Foundations of Data Analytics & Visualization

Module 1: Introduction to Data Analytics

What is Data Analytics? Why is it Important?

Real-world examples across industries

The Data Analytics Lifecycle/Process Overview

Roles in Data Analytics (Analyst, Scientist, Engineer etc.)

Ethical considerations in data handling

Module 2: Understanding Data

Types of Data (Quantitative vs. Qualitative, Structured vs.Unstructured)

Common Data Sources (Databases, Spreadsheets, APIs, Web)

Introduction to Data Quality (Accuracy, Completeness,Consistency)

Basic Data Exploration Concepts

Module 3: Fundamentals of Data Analysis & Statistics

Introduction to Descriptive Statistics (Mean, Median, Mode, Range)

Understanding Distributions (Basic Concepts)

Introduction to Correlation vs. Causation

Hands-on Activity: Calculating basic stats using sample data (e.g., in Excel/Google Sheets)

Module 4: Introduction to Data Visualization

Why Visualize Data? Principles of Effective Visualization

Common Chart Types (Bar, Line, Pie, Scatter Plot) and When to Use Them

Introduction to Dashboards: Purpose and Key Components

Understanding Key Performance Indicators (KPIs)

Activity: Critiquing visualizations & sketching dashboard ideas

Day 2: Applying Analytics & Communicating Insights

Module 4: Data Visualization & Dashboards (Continued)

Building Basic Dashboards: Concepts and Tools Overview (e.g., demonstrating simple dashboard creation in Excel/GoogleSheets or a tool like Tableau Public/Power BI Desktop)

Integrating multiple data sources conceptually

Activity: Designing a simple KPI dashboard layout for a given scenario

Module 5: Introduction to Predictive Analytics & Machine Learning Concepts

What is Predictive Analytics? How does it differ from descriptive?

Basic Concepts: Forecasting, Classification, Clustering (explained simply)

Introduction to Machine Learning: What it is, how it learns from data (conceptual overview)

Examples: Recommendation engines, spam filters, sales forecasting

Understanding limitations and biases

Module 6: Communicating Analytical Outcomes

The Importance of Storytelling with Data

Tailoring communication to your audience (Technical vs. Non-technical)

Structuring a data presentation or report

Techniques for simplifying complex findings

Activity: Practice explaining insights from a simple chart/table

Module 7: Designing Data-Driven Solutions

Framing Business Challenges as Data Questions

Case Study: Walking through a simplified business problem and how data analysis & visualization could provide solutions/insights

Group Activity: Brainstorming data approaches for sample business scenarios

Frequently Asked Questions

What is Generative AI for Content Creation?

Generative AI for Content Creation refers to using AI tools to generate or enhance content such as images, videos, voiceovers, music, narration, and other creative assets from prompts and reference materials.

How can Generative AI help with content creation?

Generative AI can accelerate ideation and production by helping users create images, video concepts, voiceovers, music, and other content assets. It can also automate repetitive production workflows and generate multiple content variations.

Can beginners learn AI content creation without technical skills?

Yes. The course is designed for content creators, marketing teams, designers, social media managers, and business professionals, with practical exercises focused on prompting, creative production, and workflow automation rather than traditional programming.

Can Generative AI create videos and voiceovers?

Yes. The course covers prompt-to-video, image-to-video, AI voiceover, narration, music, sound design, voice cloning, and multilingual dubbing. Participants also learn about the current limitations of AI-generated video and audio.

What tools are used in this Generative AI content creation course?

The course introduces platforms and tools including Figma Weave, Krea, OpenArt, AI image and video models, and dedicated audio tools. Examples covered include ChatGPT Images, Nano Banana, Imagen, Veo, Seedance, Kling, ElevenLabs, and Minimax.

Is AI-generated content safe to use commercially?

AI-generated content may involve copyright, attribution, licensing, privacy, and confidentiality considerations. The course teaches participants how to identify these risks and apply responsible practices when creating content for commercial use.

Is this course HRDC Claimable?

Yes, the course can be offered as an HRDC claimable training programme, subject to applicable HRDC requirements, approval, and the employer's eligibility.

Can this Generative AI content creation course be customized?

Yes. The course can be customized around an organization's content requirements, brand guidelines, target audiences, preferred AI tools, and real-world content production workflows.

ADAV-DO: Advanced Data Analytics And Visualization

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