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KPMG Emerging Tech Training February

KPMG Emerging Tech Training February

Price
Regular price $55.00 Sale

Snapshot

Duration:
Time:
Delivery:
3 Days
9:00am-5:00pm each day
Instructor-led
50% Lecture
Ways to Train: Public Classroom
Instructor-led Virtual
Onsite at Your Location
50% Lab

Who BTA Trains

Course Details (Click below to expand)

February 12th

Morning Session - Connectivity and Data

Internet of things (IoTs)
  • The interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data.
  • What is it and how does it work?
  • Use Cases and Implications

 

Mobility and Ambient computing

  • As the IoT landscape populates with smarter devices and the data they generate, ambient computing is the fabric that knits them together.
  • What is it and how does it work?
  • Use Cases and Implications
  • Q & A

Afternoon Session Cloud and Saas

  • Software as a service (SaaS) is a software distribution model in which a third-party provider hosts applications and makes them available to customers over the Internet. SaaS is one of the main categories of cloud computing.
  • What is Cloud and how does it work?
  • What is Saas and how does it work?
  • Saas is delivered to the users from the cloud
  • Use Cases and Implications
  • Q & A

February 14th

Morning Session- Blockchain Basics

  • A distributed ledger or shared database that keeps a record of transactions/data
  • What is it ?
  • How does it work?
  • Benefits and Draw Backs and how is it different from todays technology?
  • Q & A

Afternoon Session- Introduction to Blockchain Architectures

  • There are various blockchain models emerging that each offer different business solutions.
  • A deeper look at different types of blockchains
  • Use Cases and Implications for the different blockchain architectures
  • Q & A

February 19th

Morning Session -Data Analysis

Advanced  Data Visualization

  •  A sophisticated technique, typically beyond that of traditional Business Intelligence, that uses “the autonomous or semi-autonomous examination of data or content to discover deeper insights, make predictions, or generate recommendations.
  • What is it and how does it work?
  • Use Cases and Implications
Data Insights
  • data is the collected information, analytics is understanding that information, and insights is what you gain after understanding what it all means for your company.
  • What is it and how does it work?
  • Use Cases and Implications
  • Q & A
        

Afternoon Session- Data Engineering

  • Transforming data into a useful format for analysis.
  • What is it and how does it work?
  • Use Cases and Implications
  • Q & A

February 21st

Morning Session- Machine Learning

  • Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
  • What is it and how does it work?
  • Use Cases and Implications
  • Q & A

Afternoon Session - Deep Learning

  • Deep learningis part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.
  • What is it and how does it work?
  • Use Cases and Implications
  • Q & A

February  26th

Morning Session- NLP and Intelligence

Image, Text, Speech, Natural Language Intelligence

  • Building systems that can understand language/text/image. It is a subset of Artificial Intelligence.
  • What is it and how does it work?
  • Use Cases and Implications
Cognitive search and Chat bots
  •  Chatbots can be built  using cognitive services, as cognitive computing will empower the chatbot with a certain level of intelligence in communication like understanding the user’s needs based on their previous communication, recommendations given and more.
  • What is it and how does it work?
  • Use Cases and Implications
  • Q & A

Afternoon Session- Robotics Process Automation and Dynamic Workflow

  • Robotics Process Automation, coupled with machine learning, natural language processing, and analytics, extends the reach and range of automation from tasks and activities to driving dynamic workflow engines.
  • What is it and how does it work?
  • Use Cases and Implications
  • Q & A