Data Science & Visualization

Get Data Science Visualization Certified

Wed: 12 October, 2022 -LIVE!
Or...Wed: 26 April, 2023 - LIVE!
Live, Virtual or On-Demand
LON, Dubai, Singapore, Sydney
US$2997 / person before 01 July
US$4997 / person AFTER 01 July

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before 01 July !

AS A MEMBER, YOU WILL GET...
FREE Expert Consultation
FREE Best-Practice Case Studies
FREE Done-For-You Solutions
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FREE Intros to NEW CLIENTS
FREE Webinars & Whitepapers
FREE VIP Discount Vouchers!

Why attend now?

Data Science is one of the most demanding skills in the 21^st century, with promising high-paying jobs in Big Tech with the likes of Google, Microsoft, Facebook, LinkedIn, Amazon and more.

According to the U.S. Bureau of Labor Statistics, the number of jobs in Data Science will increase by 28% within 2026, adding more than 11.5 million new jobs with an average salary of $124k+

This Masterclass has been designed through months of research and analysis to prepare learners as pioneers in the Data Science industry and revolutionize the field by applying the data science skill today’s world demands.

On completion, you’ll achieve the prestigious, globally-recognized Certified Masters Diploma Badge and the professional qualification of Certified Data Science & Visualization (CDSV) to put on your business card and career biography.

Data Science/Visualization: applied case studies, tools. Learn From The Best!

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What you'll Gain

The data have started getting recognition as the fuel of industry 4.0 and a data-centric economy, boosting the emergence and rapid development of Data Science as one of the top IT skills of the 21^st century.

This programme gives you everything you need to master this discipline and thrive as a potential Data Science and Visualization specialist equipped with all the skills and knowledge today’s world demands.

FORMAT/LOCATION

One-Day Masterclass Summit

WHEN

26 Oct, 2022 or

26 April 2023

9am-6pm

Or On-Demand

AWARD

Certified Data Science & Visualization (CDSV)

Masterclass Schedule

Live Agenda

Tailor-Made For You!

This Masterclass will be presented by up to two members of our Expert Masters Faculty Panel.

See their expert credentials below

This format ensures that we focus on meeting your unique needs. So you get the most relevant practitioners to help you get certified as a leading professional in this high-growth sector.

09.00 – 11am

Session 1

The Origin, Trends, and Future of Data Science – Hoax VS. Reality with Solid Foundation

The origin, current trends, future of data science
What is and what isn't in data science
The key points and strategies to understand the dataset
Discovering the tools and tactics applicable to the dataset
Identifying the boundaries of expectation from a dataset
Interactive exercise with the popular dataset
Discussion and opinion sharing

Morning Networking Break at 10:30am

11:00 – 12:00pm

Session 2

Data Science and Visualization – Applied Statistics

What are Data, Data Science, and beyond
Dealing with data using the principle of statistics
Data Visualization – bars, charts, pies, boxes, and more
Interactive exercise to identify appropriate visualization methods for different types of data
Discovering central and scatter tendency
Exercise on plotting the tendencies
Estimation analysis through exercise

12.00-1:30pm

Networking Lunch for Delegates & Guests

1.30 – 2.30pm

Session 3

Grouping and Analysis as Professional Data Scientists

Necessity, application, and effectiveness of data grouping
Mean & variance test – F-test, Chi-square test, Levene, ANOVA table, Welch correction
The step-by-step practice of mean & variance testing using the popular datasets
Exploring different comparison methods – general, Bonferroni, and Tukey-Kramer
Training on storytelling in Tableau
Exercise on data grouping and comparison analysis

2:30-3:00pm

Networking Break

3:00 – 4:00pm

Session 4

Linear Regressions and Applications

Application and effectiveness of linear regressions in data science and visualization
Linear equation and mapping to univariate and multivariate linear regressions
Intuitive discussion on data patterns and applicability of linear regressions
Linear regressions validation criteria and tactics
Step-by-step practice in regression model testing
R VS. R square interpretation and ANOVA table analysis
Hands-on training – application of linear regression in data analysis and visualization
Demonstration of discovering solutions through linear regressions

4:00-4:30pm

Networking Break

4:30 – 6:00pm

Session 5

Logistic Regressions and Applications

The application domain of logistic regressions in data science and visualization
Hypothesis formation and the core concept behind different logistic regression algorithms
Interactive practice session on hypothesis formation
The art and strategies of selecting an appropriate predictive model for different datasets
Hands-on practice of implementing and evaluating predictive models
The ins and outs of model evaluation
Demonstration of discovering solutions through logistic regressions

4:30 – 6:00pm

Session 6

Practical Data Science – Working on Projects

Case study on practical data science projects
Training on Power BI to visualize data
Discovering the best practices – Question, Design, Preview, Analyze, Review, Finalize
Applying the appropriate sampling method
Interactive exercise on the selected data science project
Data Science Project Management – Effectiveness of Agile, Scrum, and Kanban
Interactive discussion and opinion sharing on the future of Data Science.

Who Should Attend?

Data Science & Visualization Experts

Expert Data Science Panel:

Kirill Eremenko is a globally renowned Data Science instructor. He has guided more than 1,300,000 (1.3 million) students worldwide in Data Science and Artificial Intelligence. He has experience working as an analyst in Deloitte Decision Science & Analytics, data scientist in Sunsuper, show host in SuperDataScience Careers Podcast, and data science instructor in Udemy. He is also the founder of DataScienceGO and SuperDataScience. Currently, he is holding the position of CEO of SuperDataScience. It is an online educational portal for Data Scientists with the mission to 'Make The Complex Simple.'

Bernard Marr is one of the world's most respected business performance, digital transformation, and intelligent use of data experts. According to LinkedIn, Bernard is one of the world's top 5 business influencers. He has worked with and advised many of the world's best-known organizations, including Accenture, Astra Zeneca, Bank of England, Barclays, BP, Cisco, CRH, DHL, Fujitsu, Gartner, HSBC, IBM, Jaguar Land Rover, Mars, Ministry of Defence, Microsoft, NATO, The Home Office, NHS, Oracle, Orange, Tetley, T-Mobile, Toyota, Royal Air Force, SAP, Shell, the United Nations, Vodafone, Walgreens Alliance Boots, Walmart, among many others. He is the author of 15 books and hundreds of high profile reports and articles, including the international best-sellers 'Data Strategy,' 'Big Data in Practice,' 'Big Data,' 'Key Business Analytics,' 'Key Performance Indicators,' 'The Intelligent Company,' 'Managing and Delivering Performance' and 'Strategic Performance Management. His books have been translated into over 20 languages. They have earned numerous Amazon No one bestselling positions, the CMI Management Book of the Year award, the Axiom book award, and the WHSmith best business book award.

Gregory Piatetsky-Shapiro is a globally recognized expert in Business Analytics, Data Mining, and Data Science. He has more than 60 publications on data mining and college discovery. He also edited numerous books written on similar topics. According to LinkedIn Top Voices in 2018, the was no. 1 on Data Science and Analytics. He is the founder of KDnuggets and was president from 2001 to 2021. He is also the co-founder of KDD (Knowledge Discovery and Data Mining Conferences).

Anand is the Chief Data Scientist at Gramener.com. The flagship product of the Gramener is the Gramener Visualization Server. Under the lead of Anand, his team discovers valuable insights from data and communication and represents them as visual stories. He also led and advised teams to design IT systems for globally recognized companies like Citigroup, Honda, IBM, Target, etc. He has worked at IBM, Lehman Brothers, The Boston Consulting Group, and Infosys Consulting.

Yann André LeCun is the VP & Chief AI scientist at Meta. He is also the Silver Professor of the Courant Institute of Mathematical Sciences. He is popular as one of the three "Godfathers of AI" and "Godfathers of Deep Learning." He is the founding father of convolutional nets. He is also the Turing award (2019) and prestigious Golden Plate Award (2019) of the American Academy of Achievement winner.

Nando De Freitas is a computer scientist and leads for machine learning team in Google DeepMind. His role as principal scientist at Google DeepMind is to make technologies available to the public to maximize benefits while ensuring safety and ethics. He is also a professor of computer science at Oxford University. His study focuses on neural networks, Bayesian optimization and inference, and deep learning.

His data mining consultancy Elder Research has drawn global attention. John Elder is the CEO of Codemy.com and founder and globally recognized for developing the earliest web advertisement network bannerclicks.com. He also built the vitalBio.com, a b2b web portal. The award-winning Submission-Spider search engine is also his creation.

Dr. John Elder authored three popular books - the Handbook of Statistical Analysis and Data Mining Applications, Ensemble Methods in Data Mining, and Practical Text Mining. He also works as an adjunct professor at the University of Virginia, where he teaches data mining optimization.

Usha Rengaraju is the Principal Data Scientist at Polymath. She is also the founder of NeuroAI. Her expertise as a Data Scientist in Quantitative Finance has brought her fame as one of the top ten Data Scientists in India for 2020. Her expertise encompasses Probabilistic Graphical Models, Machine Learning and Deep Learning, and Quantitative Finance. She is also the curriculum designer of BITS Pilani's master's in Data Science program (consumed by 20,000+ students) and Upgrad's PGP program in DS (consumed by 10,000+ students).

Key Takeaways and Learning Outcomes

How to trace the origin, inspect the present, and predict the future of data science and its application.

How to trace the origin, inspect the present, and predict the future of data science and its application.
How to understand any dataset
Which tools and technologies to use for different types of datasets
How to discover the boundaries of a dataset
How to apply the concept of statistics in data science to visualize data
How to work on data as a professional data scientist
How to use machine learning algorithms to analyze data and discover valuable knowledge
How to manage data science projects as experienced data science professionals