The keynote speaker for this workshop was Dr Anuradha Chug, Associate Professor, USICT, GGSIP University, Delhi. The workshop was started with a brief introduction to “Smart Farming”, innovation, sustainability and digital transformation of agriculture. Smart farming is based on data from sensors, cloud platform storage and data analytics, all three concepts need to be implemented. The data is collected from different sensors and stored in a cloud-based back end support, which is then analyzed using proper analytics techniques, and then the relevant information is transferred to a user interface, which naturally supported the decision to conclude. The IOT applications mainly use sensors to monitor the situation, which collects a huge amount of data every day, so in the case of the Internet of Things (IOT) application, sensors contribute more. Data analytics requires data storage, data aggregation, data processing and data extraction. In order to extract information from the dataset, we need to use data mining techniques; it plays a significant role in the selection-making process on several agricultural issues. The motive behind this workshop was to give the live exposure to the students on smart agriculture sector. The session aimed to give the live demonstration and practical knowledge by applying machine learning using the IOT Data Analytics in agricultural sector. The use of machine learning and IOT in agriculture mainly reduces problems, predicts crops, predicts yield manages livestock, detects leaf diseases, recognizes crops and detects disease early. The session started from the very basics of machine learning and IOT. Total 92 students (29 MCA & 63 BCA) and 23 faculties (UG/PG) attended this workshop.. Dr Anuradha Chug and her team members gave the demonstration of data collection using sensors, loggers. The entire session was extremely informative and practically beneficial for students. It not only gave them an insight on the topic but also gave the live demo to collect the information regarding data through Data Loggers, Sensors. Overall it proved to be a two way interaction in which students were very comfortable with the speaker and asked their queries without hesitation. Dr. Chug and her team members answered all the queries very calmly and properly.