The series of MaGIC Tech Talks comes to a close with catalysing the public's awareness on Data Discovery and Augmented Analytics adoption in Malaysia. Aligned with the MySTIE framework, the focus of this session is to introduce use cases, benefits, emerging trends and equip participants with fundamental practical learning; familiarising themselves with the new emerging concepts, how the players industry operates and essentially evaluate the need for Data Discovery and Augmented Analysis when operating a startup.
Understanding Data Analysis
- Introduction to Machine Learning
- Predictive, Prescriptive and Descriptive Analytics
- Frameworks for building ML systems
- CRISP-DM
- Practical example of data analytics
- Case Studies
Visualising Data Analytics
- Why TABLEAU?
- Simplifying and sorting your data
- Measure names and measure values
- Business calculations
- Data Analytics using TABLEAU
- Case Studies
Augmented Analytics
- Augmented Intelligence vs Augmented Analytics – what is it?
- Technology infrastructure to support Augment Intelligence
- Building models to support Augment Intelligence
- Augment Intelligence in a Business Process
- Risks in Augment Intelligence
- What techniques makeup Augmented Analytics
- Usage of Augmented Analytics in today's Organizations
- Why is Augmented Analytics key to success today
- How can TABLEAU Augmented Analytics power up your decision making
Data Science
- Categories of Data Science
- Data science as an umbrella term
Artificial Intelligence
- AI vs Data Science
- Impact of AI in Real-time
- Slicing the AI Space
Machine Learning
- What is Machine Learning?
- Types of Machine Learning
- Supervised and Unsupervised Learning
Deep Learning
- Deeper Dive into Deep Learning
- Artificial Neural Network
NLP
- Components of NLP
- NLP in today’s era
The series of MaGIC Tech Talks comes to a close with catalysing the public's awareness on Data Discovery and Augmented Analytics adoption in Malaysia. Aligned with the MySTIE framework, the focus of this session is to introduce use cases, benefits, emerging trends and equip participants with fundamental practical learning; familiarising themselves with the new emerging concepts, how the players industry operates and essentially evaluate the need for Data Discovery and Augmented Analysis when operating a startup.
Understanding Data Analysis
- Introduction to Machine Learning
- Predictive, Prescriptive and Descriptive Analytics
- Frameworks for building ML systems
- CRISP-DM
- Practical example of data analytics
- Case Studies
Visualising Data Analytics
- Why TABLEAU?
- Simplifying and sorting your data
- Measure names and measure values
- Business calculations
- Data Analytics using TABLEAU
- Case Studies
Augmented Analytics
- Augmented Intelligence vs Augmented Analytics – what is it?
- Technology infrastructure to support Augment Intelligence
- Building models to support Augment Intelligence
- Augment Intelligence in a Business Process
- Risks in Augment Intelligence
- What techniques makeup Augmented Analytics
- Usage of Augmented Analytics in today's Organizations
- Why is Augmented Analytics key to success today
- How can TABLEAU Augmented Analytics power up your decision making
Data Science
- Categories of Data Science
- Data science as an umbrella term
Artificial Intelligence
- AI vs Data Science
- Impact of AI in Real-time
- Slicing the AI Space
Machine Learning
- What is Machine Learning?
- Types of Machine Learning
- Supervised and Unsupervised Learning
Deep Learning
- Deeper Dive into Deep Learning
- Artificial Neural Network
NLP
- Components of NLP
- NLP in today’s era
List the various categories of Data Science and the importance of data science in various fields.
Provide awareness in AI and explain the various applications of AI techniques.
Discuss the various machine learning models.
Describe deep learning models and artificial neural networks.
Discuss NLP concepts in deep learning.
Innovative, quality and result-driven oriented Data Scientist with 26 years of experience executing data-driven solutions to increase efficiency, accuracy and utility of internal data processing. Dr. Suresh is experienced in creating predictive data models, BeSpoke ML?DL algorithms for efficient AI and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems. Skills include: AI/ML/DL, Big Data Queries & Interpretation, Decision Analytics, Data Mining & Visualisation Tools, Predictive Modeling, Business Intelligence (BI) using TABLEAU, KPI Dashboard & BPI Plans, Imagineered Data Scientist in R, PYTHON & JULIA.