Credence Robotics | Home Automations | Agriculture Automations | Artificial Intelligence

Credence Robotics in Association with VISIO AI Organizes a series of 3 Days Workshop on Artificial Intelligence in the month of January 2018. It is An effort to empower a new cohort of AI Engineers who will use Artificial Intelligence in Ethical ways to enhance their career and to find solutions for Global Humanitarian Challenges.


Batch 2: 18th January 2018 - 20th January 2018

  • Advanced Automation with self Learning Capabilities.
  • Swift and Accurate Results.
  • WIDE Range of Applications.
  • Utilize Zetta Bytes of Data in to something useful and gain a better insights into assets and personal Management.
  • Transform Relationship between Humans and Machines.
  • Studying AI now can enhance your career opportunities a software engineer researching neural networks, human-machine interfaces, and quantum artificial intelligence.


  • 3-6 Months Internship (For Selected Participants) with VISIO AI and Credence Robotics to work on the Real-Time Projects.
  • Mentorship for Personal Projects on Artificial Intelligence and Robotics.
  • Full-Time Work Opportunities with VISIO AI and Credence Robotics post Internship (Only for selected Interns).
  • 10% OFF on workshop fee if you organize our workshops (Robotics, Internet of Things and Artificial Intelligence) in your Institution/Organization.
  • By 2025, Work automation will lead to a net loss of 9.1 million Jobs in IT Sector.
  • By the end of this year, there will be 6.4 billion connected gadgets worldwide. As most of companies start using IoT solutions for business purposes, the amount of data generated by smart sensors increases (and will reach 400 zettabytes by 2018). Thanks to Artificial Intelligence, we can boil this data down to something meaningful and gain a better insight into asset and personnel management.
  • Facebook uses machine learning algorithms to track user behavior and improve ad targeting.
  • With Artificial Intelligence, marketers can automate a great share of routine tasks, acquire important data and devote more time to their core responsibilities — that is, increasing revenues and customer satisfaction.

    Linear regression was the first type of regression analysis to be studied rigorously, and to be used extensively in practical applications. This is because models which depend linearly on their unknown parameters are easier to fit than models which are non-linearly related to their parameters and because the statistical properties of the resulting estimators are easier to determine.


    In machine learning, the perceptron is an algorithm for supervised learning of binary classifiers (functions that can decide whether an input, represented by a vector of numbers, belongs to some specific class or not).[1] It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.


    Logistic regression is the appropriate regression analysis to conduct when the dependent variable is dichotomous (binary).  Like all regression analyses, the logistic regression is a predictive analysis.  Logistic regression is used to describe data and to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables.


    In information technology, a neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural networks -- also called artificial neural networks -- are a variety of deep learning technologies.


    A Convolutional Neural Network (CNN) is comprised of one or more convolutional layers (often with a subsampling step) and then followed by one or more fully connected layers as in a standard multilayer neural network. The architecture of a CNN is designed to take advantage of the 2D structure of an input image (or other 2D input such as a speech signal).


    The Bayesian Paradigm can be seen in some ways as an extra step in the modelling world just as parametric modelling is. We have seen how we could use probabilistic models to infer about some unknown aspect either by confidence intervals or by hypothesis testing.

    Before purchasing tickets, carefully review your event and ticket selection. NO REFUND OR EXCHANGE ON ANY TICKET will be given or service fee except during cancellation or rescheduling, or relocation of an event by CREDENCEROBOTICS LLP given that the customer has requested the refund within a reasonable time and provide valid proof of purchase. Refund liability is limited to the first 10 requests and not post this. CREDENCEROBOTICS LLP cannot offer you a refund when it’s 72 hours to the event and if you can no longer attend an event or any personal circumstances, however you may give your tickets to another person to use( based on mail and confirmation from authentic source). Name changes policies may vary on an event basis. Please check specific event terms of service regarding name changes. CREDENCEROBOTICS LLP will not replace lost, stolen or damaged hard copy tickets. Lost e-tickets can be re-issued to owners to the initial email address used to purchase the tickets minimum 48 hours prior the event.

  • Carry Your Laptop to the Workshop venue.

  • You MUST Know either C Language or Python (Recommended) to understand the programming concepts during the workshop. Ask us If you Require any Materials to Learn Basics of Python.

  • Accomodations at the nearest Hotels Will be arranged at the rate of ₹1600 Per Person Per Day.You can Opt for it during Checkout.

  • Workshop Location

    Credence Robotics, 7th Floor, Panini Block, PES University, Banashankari 3rd Stage, Hosakerehall, Bengaluru - 560085.

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