Pleased to be in the list of top 30 influencers for #IoT for 2017 along with Amazon Bosch Cisco Forrester and Gartner ..

Pleased to be in the list of top 30 influencers for IoT for 2017 along with Amazon Bosch Cisco  Forrester and Gartner ..

About 4 years ago, when I suggested to Oxford University that we should create a course on only the Algorithmic (#Datascience and #AI) aspects of Internet of Things .. I am grateful that they accepted the obscure(and complex!) idea creating the now industry recognised Data Science for Internet of Things course

Here, we work on complex and pioneering aspects of AI, Data Science and IoT (for instance systems engineering for AI/IoT).
Special thanks to Peter Holland and Adrian Stokes at Oxford University.
The list is created by Munich Re .. one of the largest reinsurance companies and Industrial IoT companies  in the world
https://en.m.wikipedia.org/wiki/Munich_Re twitter feed @relayr_iot
Great to see IoT friends  Alexandra , Ronald Van Loon, Boris Adryan, Rob Van Kranenberg also on the list

Implementing Enterprise AI course using TensorFlow and Keras

Switch your career to Artificial Intelligence(AI) in 2018 through this unique and limited-edition course focused on AI for the Enterprise.

 

The Implementing Enterprise AI course covers

  • Design of Enterprise AI services
  • Technology foundations of Enterprise AI systems
  • Specific AI use cases
  • Development of AI services using TensorFlow and Keras
  • Deployment and Business models

We use TensorFlow and Keras. We also cover deployment models using Microservices, Docker and Kubernetes.

 

More details

  • The course targets developers and Architects who want to transition their career to Enterprise AI. The course correlates the new AI ideas with familiar concepts like ERP, Data warehousing etc and helps to make the transition easier. The course is based on a logical concept called an  ‘Enterprise AI layer’. This AI layer is focused on solving domain specific problems for an Enterprise.  We could see such a layer as an extension to the Data Warehouse or the ERP system (an Intelligent Data Warehouse/ Cognitive ERP system). Thus, the approach provides tangible and practical benefits for the Enterprise with a clear business model.
  • See link below for references from previous courses
  • Duration: Starting Jan 2018 Approximately six months (3 months for the content and up to three months for the Project)
  • Course includes a certificate of completion for projects (Projects will be created in a team and will use the code base provided in Keras)
  • The course covers the Enterprise AI Use Cases like insurance, Fraud detection, Anomaly detection, Churn, classification, Customer analytics etc
  • We also have a strategic(non-coding) based version of the course also
  • Delivery format is via video and online sessions (once every two weeks)
  • For pricing please contact us below

Please contact us to sign up or to know more [email protected]

Testimonials for our courses

 

 Jean Jacques Bernand – Paris – France

“Great course with many interactions, either group or one to one that helps in the learning. In addition, tailored curriculum to the need of each student and interaction with companies involved in this field makes it even more impactful.

As for myself, it allowed me to go into topics of interests that help me in reshaping my career.”

 

Johnny Johnson, AT&T – USA

“This DSIOT course is a great way to get up-to-speed.  The tools and methodologies for managing devices, wrangling and fusing data, and being able to explain it are taking form fast; Ajit Jaokar is a good fit.  For me, his patience and vision keep this busy corporate family man coming back.”

 

Yongkang Gao, General Electric, UK.

“I especially thank Ajit for his help on my personal project of the course — recommending proper tools and introducing mentors to me, which significantly reduced my pain in the beginning stage.”

 

karthik padmanabhan Manager – Global Data Insight and Analytics (GDIA) – Ford Motor Pvt Ltd.

“I am delighted to provide this testimonial to Ajit Jaokar who has extended outstanding support and guidance as my mentor during the entire program on Data science for IoT. Ajit is a world renowned professional in the niche area of applying the Data science principles in creating IoT apps. Talking about the program, it has a lot of breadth and depth covering some of the cutting edge topics in the industry such as Sensor Fusion, Deep Learning oriented towards the Internet of things domain. The topics such as Statistics, Machine Learning, IoT Platforms, Big Data and more speak about the complexity of the program. This is the first of its kind program in the world to provide Data Science training especially on the IoT domain and I feel fortunate to be part of the batch comprising of participants from different countries and skill sets. Overall this journey has transformed me into a mature and confident professional in this new space and I am grateful to Ajit and his team. My wish is to see this program accepted as a gold standard in the industry in the coming years”.

 

Peter Marriott – UK – www.catalystcomputing.co.uk

Attending the Data Science for IoT course has really helped me in demystifying the tools and practices behind machine learning and has allowed me to move from an awareness of machine learning to practical application.

 

Yair Meidan Israel – https://il.linkedin.com/in/yairmeidandatamining

“As a PhD student with an academic and practical experience in analytics, the DSIOT course is the perfect means by which I extend my expertise to the domain of IoT. It gradually elaborates on IoT concepts in general, and IoT analytics in particular. I recommend it to any person interested in entering that field. Thanks Ajit!”

 

Parinya Hiranpanthaporn, Data Architect and Advanced Analytics professional Bangkok

“Good content, Good instructor and Good networking. This course totally answers what I should know about Data Science for Internet of Things.”

 

Sibanjan Das – Bangalore

Ajit helped me to focus and set goals for my career that is extremely valuable. He stands by my side for every initiative I take and helps me to navigate me through every difficult situation I face. A true leader, a technology specialist, good friend and a great mentor. Cheers!!!

 

Manuel Betancurt – Mobile developer / Electronic Engineer. – Australia

I have had the opportunity to partake in the Data Science for the IoT course taught by Ajit Jaokar. He have crafted a collection of instructional videos, code samples, projects and social interaction with him and other students of this deep knowledge.

Ajit gives an awesome introduction and description of all the tools of the trade for a data scientist getting into the IoT. Even when I really come from a software engineering background, I have found the course totally accessible and useful. The support given by Ajit to make my IoT product a data science driven reality has been invaluable. Providing direction on how to achieve my data analysis goals and even helping me to publish the results of my investigation.

The knowledge demonstrated on this course in a mathematical and computer science level has been truly exciting and encouraging. This course was the key for me to connect the little data to the big data.

 

Barend Botha – London and South Africa – http://www.sevensymbols.co.uk

This is a great course for anyone wanting to move from a development background into Data Science with specific focus on IoT. The course is unique in that it allows you to learn the theory, skills and technologies required while working on solving a specific problem of your choice, one that plays to your past strengths and interests. From my experience care is taken to give participants one to one guidance in their projects, and there is also within the course the opportunity to network and share interesting content and ideas in this growing field. Highly recommended!

- Barend Botha

 

Jamie Weisbrod – San Diego - https://www.linkedin.com/in/jamie-weisbrod-3630053

Currently there is a plethora of online courses and degrees available in data science/big data. What attracted me to joining the futuretext class “Data Science for ioT” is Ajit Jaokar. My main concern in choosing a course was how to leverage skills that I already possessed as a computer engineer. Ajit took the time to discuss how I could personalize the course for my interests.

I am currently in the midst of the basic coursework but already I have been able to network with students all over the world who are working on interesting projects. Ajit inspires a lot of people at all ages as he is also teaching young people Data science using space exploration.

 

 Robert Westwood – UK – Catalyst computing
“Ajit brings to the course years of experience in the industry and a great breadth of knowledge of the companies, people and research in the Data Science/IoT arena.”

Companies / Participants who have been part of the course

 

Tech: GE, HPE, Oracle, TCS, Wipro, HCL, HPE, Dell, Honeywell

Banking and Fintech : Goldman Sachs, ABN Amro, Nordea, Santander, BNP Paribas

Telecoms : Nokia, AT&T, Ericsson

Consulting : McKinsey, PA consulting

Automotive : Ford, Daimler, Jaguar

Retail : Coca Cola, Target

Airlines and Aircrafts : Boeing, Airbus

(Note : Above list includes participants from companies and also companies who have sponsored their personnel)

Participant Countries

We are pleased to have participants from all over the world – leading to a vibrant and a diverse learning ecosystem. A majority of our participants are from UK USA and India. But we also have participants from the following

North America: USA, Canada

Europe:  UK and Eastern Europe:  UK, Germany, France, Belgium, Poland, Russia, Norway, Italy, Finland, Ukraine, Austria, Ireland, Spain, Estonia, Sweden, Switzerland, Russia, Holland

Asia:  India, Japan, Thailand, Vietnam, Singapore

Middle East: UAE, Egypt, Iran

South America: Mexico, Brazil, Colombia, Nicaragua

Africa: South Africa, Zimbabwe

Australia and NZ: Australia

 

Contact

info at futuretext dot com

Timeline and Course outline

The course has three phases: Foundations, Development and Deployment. The projects are included in the deployment phase(in groups)

The Quiz is mostly in coding exercises (Unless you choose the strategic option)

Foundations (Jan – Feb)

  • The foundations of Data Science for the Enterprise with an emphasis on emerging fields like IoT and fintech.
  • A methodology for solving AI problems for the Enterprise
  • Foundations of Python
  • Tensorflow and Keras introduction
  • An end to end application (in code) for implementing Data Science for Enterprise and IoT
  • Understanding AI and Deep Learning

Development (March – April – May)

  • Machine learning implementation in detail
  • Understanding of Deep Learning concepts and implementation
  • Algorithms (ML and DL) : Multilayer Perceptron, Auto encoders, Deep Convolutional Networks, Recurrent Neural Networks, Reinforcement learning, Natural language processing
  • Implementations covering both Time series and Image
  • Unique considerations for Enterprise AI problems
  • Unique considerations for IoT (In this section, we consider the deployment models for IoT applications both for consumer and Industrial IoT – these include Edge, Complex event processing etc)
  • Considerations for specific industry verticals - insurance, Fraud detection, Anomaly detection, Churn, classification, Customer analytics etc

Deployment (June – July)

  •  A systems thinking approach for deploying complex applications
  • Understanding Docker, Microservices, Kubernetes and their role in the deployment cycle
  • Projects(in groups in a sprint / agile cycle)

Contact

info at futuretext dot com