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Machine Learning, AI & Deep Learning Training

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Course type: Online Instructor led Course

Platform: Google

Course ID: 32603

Course type: Online Instructor led Course

Platform: Google

Students Interested 0 (Seats Left 0)

₹ 29,999

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Safi Patel

Global Head-training

About Safi Patel

Seasoned technology consultant with experience in diversified disciplines
- Passionate mentor and trainer with strong technical skills
- Experienced expert in new product development, product planning and project management
- Engineering graduate with Masters in Embedded Systems
- Research interest- Protocol development, device design & open source technologies
- 18+ Years of Experience of research, design and development in Embedded Systems, ESDM, IoT, Medical Electronics, Networking, IT and Project management.
- 10+ years of experience as skill development and corporate trainer in Embedded, Communication, and IoT domain
- Field experience of implementation of Hospital Information Systems and PACS
- Strong conceptual understanding of communication protocols: RS232C, SPI, I2C, TCP/IP, IPv4/IPv6, MQTT, CoAP, and medical imaging protocols: DICOM, HL7, PACS
- Strong programming & coding skills in Python, C and Assembly
- Strong development skills on 8051, Arduino and ARM based dvelopment platforms
- Trained more than 8000 engineering graduates
- Designed and developed hundreds of projects and product prototypes
- Certified service engineer for Siemens X-ray systems & AGFA Medical Imaging Systems (CR Systems)
- Good knowledge of PLC/SCADA & Ladder programming.
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About the Course

Machine learning methods are used for data analysis, this is where they are similar to data mining, but the main goal of machine learning is to automate decision models. Algorithms are the heart and soul of machine learning and they help computers to find hidden insights.


So in essence machine learning algorithms need to learn. The machine needs to learn from data. Data will have multi dimensions- Type (quantitative or qualitative), amount (big or small size) and number of variables available to solve a problem. Learning algorithms should also be as general purpose as possible. We should be looking for algorithms that can be easily applied to a broad class of learning problems.


The data scientists are responsible for machine learning and getting outputs but the business people are the ones who are going to use it for business purpose so the rules and insights extracted from machine learning should be interpretable. So the output produced by the machine has to be understood by humans, who may not be from the machine learning area.


What differentiates this course are the following:



  1. Case study based approach, where participants are immersed in the problem.

  2. Complete package of AI (deep learning and NLP) and machine learning.


Objectives


The training aims at providing the participants with latest and general purpose machine learning algorithms. At the same time the training aims to deliver some common threads or a common knowledge base which can be used in future for learning a wide range of algorithms.

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