AI / Datascience courses – fintech and IoT


Personalized AI /  Datascience  courses – fintech and IoT  – starting Jan 2018

I am happy to announce the next batch of personalised AI courses

1)  AI for fintech

2) AI for Internet of Things

We conduct personalised courses with limited batch size for professionals

we offer projects with hands-on experience

In our courses, we apply AI to specific vertical domains (currently AI for fintech and AI for IoT)

All our courses are conducted by me and my team

They have the following characteristics


  • Based on AI (An emphasis on Deep Learning models but also including traditional machine learning models)
  • hands-on project experience in agile/scrum format
  • Application of AI to vertical domains (currently fintech, IoT)
  • Using Tensorflow and Keras
  • Using Open source projects online which you can learn from in sprint cycles (develop code professionally)
  • Small, personalized groups
  • Personalized coaching approach for AI (you can choose an emphasis ex Blockchain within the context of the course)
  • 6 to 9 months in duration
  • Affordable




 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 –

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 –

“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 –

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 -

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


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

Banking and Fintech

Goldman Sachs, ABN Amro, Nordea, Santander, BNP Paribas


Nokia, AT&T, Ericsson


McKinsey, PA consulting


Ford, Daimler, Jaguar


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



info at futuretext dot com

Timeline and Course outline

Courses last about 6 to 9 months



  • The foundations of Data Science for IoT and how it differs from traditional data science.
  • A methodology for solving IoT projects. This methodology will consider the various options like Edge processing, Time series, Sensor fusion/Complex event processing, Streaming etc
  • An end to end application (in code) for implementing Data Science for IoT
  • Designing an IoT product
  • Understanding IoT platforms
  • Understanding IoT products and how analytics fit into it
  • Machine learning algorithms in TensorFlow and Keras:
  • QUIZ

Designing with Deep Learning algorithms

  •  Understanding AI and Deep Learning
  • An introduction to tensorflow and keras
  • 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 Images
  • QUIZ

Deploying IoT products

  •  In this section, we consider the deployment models for IoT applications both for consumer and Industrial IoT
  • These include Edge, Micoservices etc
  • A systems thinking approach for deploying complex IoT applications
  • Streaming and streaming analytics(ex Spark/Kafka)

Data Science for IoT advances/specific topics

Below is a list of IoT specific topics which we cover in the course

  • AI in IoT (time series and images based processing)
  • Time series data analysis
  • Time series feature selection
  • Time series databases
  • Knowledge discovery from Time series
  • Edge computing Hardware acceleration
  • Handling data with noise and skew
  • IoT feature engineering
  • Complex event processing
  • Multivariate time series
  • Co-relations between time series
  • Handling IoT data with Noise and Skew
  • IoT and Mobile(tensoeflow mobike and coreml)




•             Foundations of Enterprise AI

•             Understanding the application of AI for fintech

•             Introduction to TensorFlow and Keras

•             End-to-end implementation for an AI application

•             Theory of AI


At the conclusion of this stage  stage you choose a project and a problem statement to solve in a group. You will focus the rest of your studies within the context of that theme. For example, you may decide to work with Insurance (within fintech) or to explore the impact of IoT on the industry..


Concepts milestone + QUIZ

Designing an AI product for fintech

•             Basics of Designing an AI product

•             Understanding the complexities of fintech and AI design

•             Understanding Deep Learning

•             Machine learning algorithms in TensorFlow and Keras:

•             Designing with Deep Learning algorithms

Multilayer Perceptron

Auto encoders

Deep Convolutional Networks

Recurrent Neural Networks

Reinforcement learning

Natural language processing

Basics of Text Analytics


Development milestone + QUIZ

Deploying AI products for fintech

Deploying Deep Learning models on scale

Understanding fintech applications in AI from a deployment standpoint

Understanding the big Picture with Kubernetes and other platforms

Methodology for AI + fintech products

Deploying AI and fintech products


Acquiring Data and Training the Algorithm

Processing and hardware considerations

Business Models – High Performance Computing – Scaling and AI system

Costing an AI system

Creating a competitive advantage from AI

Specific considerations for fintech: ex EU payment directive (PSD2), etc.

Deployment milestone + QUIZ



info at futuretext dot com



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