This document provides information about a data science course with a focus on visual programming. The course aims to teach data science concepts and skills through interactive tools like KNIME Analytics Platform and Microsoft Power BI without requiring coding. It will cover topics like machine learning, data analytics, and business intelligence. Students will learn to perform tasks like data preparation, predictive modeling, and dashboard visualization on real-world case studies and projects from various industries. The course aims to provide students with practical skills to pursue careers in fields like data science, machine learning engineering, and business intelligence.
Masterdata - why it matters and how SmartMDM™ can help?Bilot
Could the whole organization be involved in the maintenance of the master data? Could de-centralizing be the key to agile & long lasting master data management? Customer cases & key info presented at the Breakfast Club seminar on the 18th May 2017.
Want to learn more? Download the 10 things to consider when choosing your master data governance tool -guide: http://go.bilot.fi/2017-05-SmartMDMDownload_LP-Download.html
Workshop on "Data Management - The Foundation of all Analytics" given by John Aidoo, Data Analytics Manager at Central Insurance Company, Van Wert, Ohio.
The purpose of business intelligence is to support better business decision making. BI systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data.
Industry researchers at Gartner announced in April 2012 that the worldwide business intelligence, analytics, and performance management software market surpassed the US$12 Billion level in 2011, a 16.4% increase over the previous year. This statistic is among many pointing to the need for both groups to apply what management guru Peter Senge proclaimed decades ago in The Fifth Discipline: the need for a learning organization. This presentation focuses on three learning areas for anyone in the business analytics profession. First, we analysts need to learn what the markets and industries are saying today. We discuss recent trends which show how analytics will shape the future. Second, we need to learn what group learning options are available. From industry conferences (such as the PASS BA Conference, and virtual PASS sessions) to free MOOCs (massive open online courses), we have more options available to improve our knowledge. Finally, we need to learn what leadership roles our groups can have. We can leverage social networks (including PASS) and social media -- both individually and as organizations -- to communicate passion.
Day 1 (Lecture 4): Data Science in the Retail Marketing and Financial ServicesAseda Owusua Addai-Deseh
Lecture on "A Practical Exposition of Data Science in the Retail Marketing and Financial Services" delivered by Delali Agbenyegah, Director of Data Science and Analytics, Express, Columbus OH, USA.
Masterdata - why it matters and how SmartMDM™ can help?Bilot
Could the whole organization be involved in the maintenance of the master data? Could de-centralizing be the key to agile & long lasting master data management? Customer cases & key info presented at the Breakfast Club seminar on the 18th May 2017.
Want to learn more? Download the 10 things to consider when choosing your master data governance tool -guide: http://go.bilot.fi/2017-05-SmartMDMDownload_LP-Download.html
Workshop on "Data Management - The Foundation of all Analytics" given by John Aidoo, Data Analytics Manager at Central Insurance Company, Van Wert, Ohio.
The purpose of business intelligence is to support better business decision making. BI systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data.
Industry researchers at Gartner announced in April 2012 that the worldwide business intelligence, analytics, and performance management software market surpassed the US$12 Billion level in 2011, a 16.4% increase over the previous year. This statistic is among many pointing to the need for both groups to apply what management guru Peter Senge proclaimed decades ago in The Fifth Discipline: the need for a learning organization. This presentation focuses on three learning areas for anyone in the business analytics profession. First, we analysts need to learn what the markets and industries are saying today. We discuss recent trends which show how analytics will shape the future. Second, we need to learn what group learning options are available. From industry conferences (such as the PASS BA Conference, and virtual PASS sessions) to free MOOCs (massive open online courses), we have more options available to improve our knowledge. Finally, we need to learn what leadership roles our groups can have. We can leverage social networks (including PASS) and social media -- both individually and as organizations -- to communicate passion.
Day 1 (Lecture 4): Data Science in the Retail Marketing and Financial ServicesAseda Owusua Addai-Deseh
Lecture on "A Practical Exposition of Data Science in the Retail Marketing and Financial Services" delivered by Delali Agbenyegah, Director of Data Science and Analytics, Express, Columbus OH, USA.
This is a presentation in a meetup called "Business of Data Science". Data science is being leveraged extensively in the field of Banking and Financial Services and this presentation will give a brief and fundamental highlight to the evergreen field.
Advanced Topics In Business Intelligenceguest1a9ef2
The blurring of the line between decision support systems and operational systems because of real-time warehousing, the use of Enterprise Information Integration (EII), and closed- loop business processes
Download at http://DavidHubbard.net/powerpoint - This Introduction to Business Intelligence gives an overview of how Business Intelligence fits into business strategy in general. It does not go into the specific technologies of Business Intelligence. It is meant to be used to explain Business Intelligence to those not already familiar with Business Intelligence.
Fuel for the cognitive age: What's new in IBM predictive analytics IBM SPSS Software
IBM recently launched an updated version of its predictive analytics platform. Explore the latest features, including R, Python and Spark integration and more powerful decision optimization.
What is business intelligence and where it is applicable is described in this presentation. The subject is offered as elective to BE IT students of Pune University.
When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...Birst
Organizations rely on solutions like Salesforce to run day-to-day operations and keep track of the massive amounts of data generated by daily customer interactions. As their business grows and their data analysis requirements evolve, these companies often find they need more robust reporting capabilities than what Salesforce offers out-of-the-box.
Join industry analyst James Haight from Blue Hill Research as he presents his new research paper, “Using Birst to Increase Efficiency and Customer Insight in Salesforce,” and describes how companies are turning to business intelligence solutions like Birst to help decision-makers glean greater insight from Salesforce data and deliver increased value to customers.
In this webinar, you will learn:
How a leading health insurance provider recognized it reached the upper limits of Salesforce reporting
The factors this organization considered when choosing a business intelligence solution
How this company transformed its business operations with greater efficiency and deeper customer insight.
This publication seeks to explain what business intelligence is, its history, usage in modern business operations and prospects into the future of BI.
The publication also mentions relevant software tool that help deliver business intelligence solutions.
PYTHON AND DATA SCIENCE FOR INVESTMENT PROFESSIONALSQuantUniversity
Join CFA Institute and QuantUniversity for an information session about the upcoming CFA Institute Professional Learning course: Python and Data Science for Investment professionals.
This is a presentation in a meetup called "Business of Data Science". Data science is being leveraged extensively in the field of Banking and Financial Services and this presentation will give a brief and fundamental highlight to the evergreen field.
Advanced Topics In Business Intelligenceguest1a9ef2
The blurring of the line between decision support systems and operational systems because of real-time warehousing, the use of Enterprise Information Integration (EII), and closed- loop business processes
Download at http://DavidHubbard.net/powerpoint - This Introduction to Business Intelligence gives an overview of how Business Intelligence fits into business strategy in general. It does not go into the specific technologies of Business Intelligence. It is meant to be used to explain Business Intelligence to those not already familiar with Business Intelligence.
Fuel for the cognitive age: What's new in IBM predictive analytics IBM SPSS Software
IBM recently launched an updated version of its predictive analytics platform. Explore the latest features, including R, Python and Spark integration and more powerful decision optimization.
What is business intelligence and where it is applicable is described in this presentation. The subject is offered as elective to BE IT students of Pune University.
When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...Birst
Organizations rely on solutions like Salesforce to run day-to-day operations and keep track of the massive amounts of data generated by daily customer interactions. As their business grows and their data analysis requirements evolve, these companies often find they need more robust reporting capabilities than what Salesforce offers out-of-the-box.
Join industry analyst James Haight from Blue Hill Research as he presents his new research paper, “Using Birst to Increase Efficiency and Customer Insight in Salesforce,” and describes how companies are turning to business intelligence solutions like Birst to help decision-makers glean greater insight from Salesforce data and deliver increased value to customers.
In this webinar, you will learn:
How a leading health insurance provider recognized it reached the upper limits of Salesforce reporting
The factors this organization considered when choosing a business intelligence solution
How this company transformed its business operations with greater efficiency and deeper customer insight.
This publication seeks to explain what business intelligence is, its history, usage in modern business operations and prospects into the future of BI.
The publication also mentions relevant software tool that help deliver business intelligence solutions.
PYTHON AND DATA SCIENCE FOR INVESTMENT PROFESSIONALSQuantUniversity
Join CFA Institute and QuantUniversity for an information session about the upcoming CFA Institute Professional Learning course: Python and Data Science for Investment professionals.
Machine Learning with Data Science Online Course | Learn and Build Learn and Build
You are just one step away from becoming a Data Scientist Engineer. Learn a foundational understanding of Machine Learning techniques at one place. Get Online Machine Learning Certification at Learn and Build.
Digicrome Data Science & AI 11 Month Course PDF.pdfitsmeankitkhan
Dive into the world of Artificial Intelligence and Data Science with Digicrome's dynamic Postgraduate Program (PGP). Our uniquely crafted curriculum blends theory with hands-on projects, led by industry experts. From cutting-edge algorithms to practical applications Artificial Intelligence Certification, elevate your skills and career prospects in today's data-driven landscape.
Using Data Science to Build an End-to-End Recommendation SystemVMware Tanzu
We get recommendations everyday: Facebook recommends people we should connect with; Amazon recommends products we should buy; and Google Maps recommends routes to take. What all these recommendation systems have in common are data science and modern software development.
Recommendation systems are also valuable for companies in industries as diverse as retail, telecommunications, and energy. In a recent engagement, for example, Pivotal data scientists and developers worked with a large energy company to build a machine learning-based product recommendation system to deliver intelligent and targeted product recommendations to customers to increase revenue.
In this webinar, Pivotal data scientist Ambarish Joshi will take you step-by-step through the engagement, explaining how he and his Pivotal colleagues worked with the customer to collect and analyze data, develop predictive models, and operationalize the resulting insights and surface them via APIs to customer-facing applications. In addition, you will learn how to:
- Apply agile practices to data science and analytics.
- Use test-driven development for feature engineering, model scoring, and validating scripts.
- Automate data science pipelines using pyspark scripts to generate recommendations.
- Apply a microservices-based architecture to integrate product recommendations into mobile applications and call center systems.
Presenters: Ambarish Joshi and Jeff Kelly, Pivotal
Data Science at Roche: From Exploration to Productionization - Frank BlockRising Media Ltd.
The excitement about the potential opportunities for leveraging data by means of advanced analytics is huge. But, the honeymoon between business and data science is over. Stakeholders want to see value generation from data science. At Roche Diagnostics the Data Science Lab was created. Its mission is to explore business opportunities for data science across the company and to deliver productive, algorithm based systems that create impact. In his keynote, Frank presented some examples of data science initiatives going from data exploration over predictive modelling to productionization. Some of the challenges encountered were addressed as well as the learnings.
Machine learning projects may seem similar to any software engineering endeavor, the reality is machine learning projects are onerous, demand high quality work from every person involved, and are sensitive to any tiny mistake.
It seems that we cannot go five years without having some massive technology shift that becomes an essential part of our day-to-day lives. So, we will start with a proper definition of machine learning and how it is changing the way businesses analyze information. We will then continue by discussing proper ways to begin machine learning projects, including weighing the feasibility of a project, planning timelines, and the stages of the machine learning workflow once you start your project.
After exploring the stages of the machine learning workflow, we will end the webinar with an example of a completed machine learning project. We will demonstrate how to create a similar project and give you the tools to create your own.
What you'll learn:
A deeper understanding of the end-to-end machine learning workflow.
The tools needed to effectively create, design, and manage machine learning projects.
The skills to define your goal, foresee issues, release models, and measure outcomes during the ML project lifecycle.
Demo: Skyl Platform for End-End machine learning workflow.
This is the slide deck for this webinar:
https://skyl.ai/webinars/guide-end-to-end-machine-learning-projects
Similar to Certified Data Science Specialist Course Preview Dr. Nickholas (20)
Significantly adopted into banking and health industries for its guaranteed transparency, Blockchain uncovers the crucial need for the integration of its technology into businesses and governmental operations.
Databases are constantly expanding, and they can potentially bring in greater revenue, increase efficiency and reduce operational costs. With the right data, businesses are able to reach their customers on a more personalized level, provided with the proper extraction of relevant insights.
Despite things rapidly shifting online, data-driven success is not easy to achieve. Most times, lack of data skills and talents become a barrier for businesses to understand and analyse these valuable data and information.
Improve customer engagement with an app for your businessiTrainMalaysia1
Moving towards a more digitally-driven customer journey, businesses are proactively trying to narrow the funnel of marketing.
With a large number of our competitors making the online shift, how can we stand out from the rest and win the hearts of our target customers?
Machine learning is the medium in which we adopt intelligence into our systems and services today. Despite the spread of successful machine learning applications we still find that there are serious challenges faced when one decides to embrace this technology. In this webinar, we will learn about the fundamentals of build a successful machine learning project. You will be able to understand the important aspects of developing functioning and sustainable intelligence.
Bagaimana Automasikan Respon Jualan Dengan WhatsAppiTrainMalaysia1
Di Malaysia , ramai penjual online masih belum menggunakan Web Jualan ecommerce. Atas faktor pengetahuan teknologi atau intra-Internet masih ada halangan bagi penjual memulakan perniagaan secara web commerce. Maka lebih ramai penjual lebih selesa menngunakan WhatsApp sebagai medium utama.
What Is Search Engine Optimization (SEO) And Why Is It Important?iTrainMalaysia1
Over 3.5 billion searches are performed on Google every day. No matter what business you are in, people are searching for your products or services on Google. But even though there are billions of searches performed every single day, studies show that 91% of pages on the Internet don’t get even a single visitor from Google. So the question is how to join the 9% club and start bringing free, consistent and passive traffic to your website from Google.
Clearing the Confusion: AI vs Machine Learning vs Deep Learning DifferencesiTrainMalaysia1
Artificial intelligence (A.I.) is imparting a cognitive ability to a machine. Machine learning (M.L.) uses algorithms to parse data, learn from that data, and make informed decisions based on what it has learned. Deep learning (D.L.) is a subfield of machine learning, it structures algorithms in layers to create an “artificial neural network” that can learn and make intelligent decisions on its own. With 4th Industrial Revolution (4IR) era and big data as fuel of the future, this webinar will explain the important difference between A.I., M.L. and D.L., their applicability, and usage in different sectors including manufacturing, supply chain and agriculture. Moreover, webinar will highlight important skills path to master them.
Python vs R for Data Science: What’s the Difference? How can they automate?iTrainMalaysia1
Businesses utilizing data to their best advantage remain competitive in the market, keeping them steps ahead from their counterparts, more evidently now when things are forced to move online.
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
2. TRAINER PROFILE
Copyright by Dr. Nickholas 2
Ts. Dr. Nickholas Anting Anak Guntor, PhD
nickholasanting.com
Professional Profile
• Lecturer in Computer Programming with Programming &
Civil Engineering at FKAAB, UTHM.
• Certified Data Science Analyst & Data Engineer by
Fusionex International.
• Author of Programming for Beginners with Python.
Data Science Project
• Concrete leakage detection with Fully Convolutional
Network for image processing.
• Predictive modelling for Projek Data Raya JPT.
• Sentiment analysis for user perception in market
analysis.
Training Fields
• Data Science with Visual Programming
• Machine Learning with KNIME
• Machine Learning with Python
• Programming with Python 3
3. THE WORLD OF DATA
Add a footer 3
Geospatial World
• Evolution of digital world has generate zettabytes and yottabytes of
structured and unstructured data every day.
• Organization took advantages from this mass amount of data and turn
it into valuable information.
• These digital data come from multiple of resources.
Online Transaction Social MediaInternet of Things
5. WHAT IS DATA SCIENCE
Add a footer 5
Definition
The field of study that dealing with data by combining multiple domain of
knowledge, including mathematics & statistics, computer programming,
analytics skill, visualization and business communication.
Probability & Statistics Computer Programming
Visualization & Business
Intelligence
Analytics Thinking
6. ANALYTICS SPECTRUM IN DATA SCIENCE
Copyright by Dr. Nickholas 6
PRESCRIPTIVE ANALYTICS
• How to make it happen?
• What is the perfect value
of discount for product A
to increase sales and
obtain high profit?
• What happened?
• Who are customers?
• How many people buy
item A?
DESCRIPTIVE ANALYTICS DIAGNOSTIC ANALYTICS
• Why does it happen?
• What cause the sales to
drop?
PREDICTIVE ANALYTICS
• What might be happen?
• If increasing the
marketing budget, will it
increase number of
sales?
7. ADVANTAGES OF SCIENCE
Copyright by Dr. Nickholas 7
PROFIT MAXIMIZATION
Apply right strategy and approach to minimize
losses and maximize profit.
FAST & BETTER DECISION
Advance tools to analyse information faster & more
accurate.
IMPROVE SERVICES
Improve customer satisfaction & experience.
NEW INNOVATION
Facilitate new product with advance features
(Self-driving car, Grab Car, Google Map)
8. CASE STUDY 1 – AMAZON.COM
Copyright by Dr. Nickholas 8
• Apply Recommendation Based System (RBS) to predict customer needs &
behavior.
• RBS used to predicts the rating or preference a user give to an item.
• 35% of revenue generated by Recommendation Engine.
9. CASE STUDY 2 – NETFLIX
Copyright by Dr. Nickholas 9
• 80% of movies watches are
recommended by system.
• Recommendation are driven
by Machine Learning
Historical Watched Movies
You may want to watch this movie.
10. CASE STUDY 3 – GPS System
Copyright by Dr. Nickholas 10
Data
Science
• AI
• Machine Learning
Digital
Technology
• Programming
• Micro-processor
11. CASE STUDY 4 – GRAB CAR
Copyright by Dr. Nickholas 11
• Improve customer service &
satisfaction.
12. DATA SCIENCE PROFESSIONAL
Add a footer 12
Data Scientist
• Profession who work with data in relevant
fields/domain industry.
• Data analytical expert with analytical thinking
and technical skill to solve complex problem.
• With mind of curiosity to explore what problem
need to be solved.
13. Add a footer 13
Are you interested to be a part of
Data Scientist team?
It might not be easy...
14. NEEDS & DEMANDS
Add a footer 14
• Demand of professional skill in data science in
industries keep increasing.
• Main challenge is to learn writing programming
code to work with Machine Learning.
• It may not be easy for someone who have no or
little programming knowledge and experience.
15. OUR INNOVATIVE DATA SCIENCE MODULE
Add a footer 15
DATA SCIENCE WITH VISUAL PROGRAMMING
A complete course on data science topic including, machine learning, data analytics and visual
programming.
• NO coding require.
• Interactive and open source
KNIME Analytics Platform software
for Machine Learning.
• Advance Microsoft Power BI tools
for data analytics and visualization.
16. VISUAL VS CODING PROGRAMMING
Copyright by Dr. Nickholas 16
Conventional Coding Visual Programming
17. WHY VISUAL PROGRAMMING
Add a footer 17
DRAG & DROP
APPROACH
NO NEED TO WRITE CODE
SCRIPTING USING
PROGRAMMING LANGUAGE.
FAST & LESS ERROR
WHILE CONSTRUCTING
THE ALGORITHM
18. KNIME ANALYTICS PLATFORM
18
• Open source visual programming tools.
• Codeless approach of performing programming task.
• Used in data analytics, manipulation, visualization & reporting.
20. DATA SCIENCE WITH VISUAL PROGRAMMING
Add a footer 20
By
Dr. Nickholas & Dr. Alvin
Data Science Course
with Visual Programming
COURSE OBJECTIVES
A complete course on data science topic including, machine
learning, data analytics with visual programming tools.
COURSE LEARNING OUTCOMES
• Understand the concept and workflow of the field of Data
Science.
• Apply the mathematics & statistics principle for data science.
• Performing data preparation based on real dataset.
• Creating machine learning algorithm for predictive modelling
using KNIME.
• Build interactive visualization & analytics dashboard using
Microsoft’s Power BI.
21. Summary of the Courses - Roadmap
Add a footer 21
MATHEMATICS
& STATISTICS
Day 2
BUSINESS
INTELLIGENCE
Day 5
MACHINE
LEARNING
Day 3 & Day 4
KNIME VISUAL
PROGRAMMING
Day 1 & Day 2
22. Course Outline
Add a footer 22
Module 1 – Introduction to Data Science
1.1 Data Science and Big Data Analytics
1.2 Discipline in the Field of Data Science
1.3 Data Analytics & Business Intelligent
1.4 Machine Learning & Artificial Intelligent
1.5 Data Science Tools.
1.6 Application of Data Science
1.7 Career Opportunities in Data Science
Module 3 – Probability & Statistics
3.1 Probability
3.1.1 Combinatory
3.1.2 Bayesian Inference
3.1.3 Distributions
3.2 Statistics
3.2.1 Descriptive Statistics
3.2.2 Inferential Statistics
3.2.3 Hypothesis Testing
Module 2 – KNIME Visual Programming
2.1 Basic KNIME Interface
2.2 Workflow & Node
2.3 Read Data File
2.4 Columns & Row Filter
2.5 Aggregation & Binning
2.6 Visualization
23. Course Outline
Add a footer 23
Module 4 – Machine Learning with
KNIME
4.1 Introduction to Machine Learning
4.2 Data Preparation & Preprocessing
4.3 Linear Regression Model
4.4 Logistic Regression Classification
4.5 Naive Bayes Classification
4.6 K-Nearest Neighbor Classification
4.7 Decision Tree Classification
4.8 Random Forest Classification
4.9 K-Means Clustering
4.10 Practical Hands-On 1
4.11 Practical Hands-On 2
4.12 Practical Hands-On 3
Module 5 – Business Intelligence with
Microsoft Power BI
5.1 Revision on Business Intelligent & Analytics
5.2 Introduction to Power BI Desktop
5.3 Query Editor
5.4 Data & Relationship View
5.5 Visualization & Dashboard Creation
5.6 Timeseries, Aggregation & Filter
5.7 Maps and Scatteplots
5.8 Creating an Interactive Dashboard
5.9 Practical Hands-On 4
24. PROJECT 1 – Student's Placement Acceptance Rate
Add a footer 24
Predictive model using machine learning for student's placement acceptance rate to
academic programme offers by higher learning institutions.
Programmed offered
• Programme 1
• Programme 2
• Programme 3
Current Application Process
Login Apply
WAITING FOR
RESULT
• Students don't have idea the chances of they being accepted for selected programme.
• Selection criteria just minimum requirement. No statistics of acceptance.
25. Machine Learning Approach
SAINS
SASTERA
Variables
• Aliran
• Jumlah A+
• Jumlah A-
• Jumlah A
• Jumlah Kredit
• Markah Kredit
• Lulus BM
• Laluan Khas
Aliran SPM Analytics & Prediction
BIDANG A
Bidang Teras NEC
BIDANG B
BIDANG C
MODEL_NEC_A
MODEL_NEC_B
MODEL_NEC_C
Predictive Model
Result
Program Matching
Keputusan Diterima
Peluang Diterima
26. Machine Learning Process for Deep Learning
NN
Train Data
80% (98560)
ML Algorithm
Test Data
20% (24640)
Apply Model
Performance AccuracyDATA CLEANING
AND PREPARATION
28. Performance Vector RUN 2
Training set
24640
true
DITERIMA
true
TIDAK_DITERIMA
Class
Precision
pred. DITERIMA 9821 2764 77.32%
pred.
TIDAK_DITERIMA
2878 9577 76.89%
MODEL ACCURACY = 77.10%
• Peratusan keputusan tepat adalah
77.10%.
• 77.32% peluang pelajar dapat
diterima sekiranya di predict
diterima.
• Cadangan supaya dapat menambah
variable seperti pilihan universiti
dan subjek A dapat meningkatkan
accuracy model.
32. PROJECT 2 – CHURN ANALYSIS
Add a footer 32
• Churn analysis for telecommunication company.
• Machine learning model to predict churn's probability of new customers.
34. Add a footer 34
Predicted 0 Predicted 1 Class Recall F-Measure
Actual 0 551 19 96.7% 0.959
Actual 1 28 69 71.1% 0.746
Class
Precision
95.2% 78.4%
Overall Accuracy 93%
• The model has high overall accuracy at 93%.
• Model has high performance to predict Churn=0 (stay) at 95.2%. Chances of customer being stay is 95.2%
when they predicted to be stayed.
• Chances of customer being churn is at 78.4%.
• F-measure in this model show that slightly different of precision & recall at 0.213 (21.3%). This is a measure
to seek the balance between Precision & Recall.
35. PROJECT 3 – CUSTOMER SEGMENTATION
Add a footer 35
• Identify the customer segment based on loyalty and satisfaction
level.
36. Add a footer 36
Clustering Model
Cluster_0
SUPPORTERS
Cluster_1
FANS
Cluster_2
ALIENATED
Cluster_3
ROAMERS
• Cluster_1 is group of
clients that are satisfy with
the shopping experience &
loyal with the product.
• Cluster_0 is group of
customers that are not
happy with the shopping
experience but they love
the brands.
• Cluster_3 is group of
customers that satisfy with
the shopping experience
but not loyal to the product.
• Cluster_2 is group of
clients that are not loyal &
satisfy.
37. Add a footer 37
StrategicAction & Communication - Prescriptive
Cluster_0
SUPPORTERS
Cluster_1
FANS
Cluster_2
ALIENATED
Cluster_3
ROAMERS
• Study on what make customer in
Cluster_0 maybe can help to
understand what probably the
cause make them not satisfy with
the shopping experience.
• To retain the customer in
Cluster_1, conduct survey on
what things can be done to
improve the service and product.
• Loyalty of customers in Cluster_3
could be improve by increasing
the loyalty program, such as
a. Membership program.
b. Discount offer.
38. SKILLS GAIN AFTER COMPLETION
Add a footer 39
• Foundation of mathematical and statistical concepts and theory in data analytics.
• Apply four main analytics spectrum – Descriptive, Diagnostic, Predictive and
Prescriptive Analytics.
• Technical skill of using KNIME Analytics Platform for building machine learning model
for predictive analytics.
• Technical skill of using Power BI to develop business intelligence dashboard.
39. Practical High Quality Hands-On
Add a footer 40
Accounting, Banking & Finance
• Churn prediction model
• Customer segmentation
• Credit risk assessment
Cyber Security
• Credit card fraud detection
Marketing & Sales
• Market demands analytics
• Forecasting
• Sales dashboard
Recommender System
• E-commerce recommender system
• Movie recommender system
40. Targeted Audience
Add a footer 41
• Marketing Manager
• Sales Manager
• Financial, Accountant & Banking Professional
• Researchers & Academician
• Engineers
• IT Professional
• Recent Graduates in Bachelor & Master Degree
41. Career Opportunities
Add a footer 42
DATA SCIENCE CERTIFICATION
• Data Scientist
• Data Science Consultant
• Machine Learning Engineer
• Machine Learning Developer
• Business Intelligent Analyst
• Business Intelligent Consultant
• Business Intelligent Developer
MACHINE LEARNING CERTIFICATION
• Machine Learning Engineer
• Machine Learning Developer
MICROSOFT POWER BI CERTIFICATION
• Business Intelligent Analyst
• Business Intelligent Consultant
• Business Intelligent Developer
42. OUR TRAINING VALUE PROPOSITION
Add a footer 43
STRUCTURED CURRICULUM FOR
REAL-BUSINESS APPLICATION
PRACTICAL CASE-STUDY WITH
REAL PROJECT FOR SPECIFIC NICHE
INDUSTRY
BUILD AUDIENCE
PORTFOLIO THROUGH
CASE-STUDY & ASSESSMENT
43. ALA - CARTE COURSE
Add a footer 44
MACHINE LEARNING WITH
KNIME ANALYTICS PLATFORM
Learn to create Machine Learning algorithm
with visual programming approach (No Coding
require)
3 – Days
BUSINESS INTELLIGENT WITH
POWER BI
Learn how to use Microsoft’s Power BI Desktop
for dashboard visualization & analytics.
2 – Days
44. Add a footer 45
Thank you very much.
Have any question?