About the FDP: 

In the latest technology trend, organizations are looking for intelligent automation tools to solve business challenges, increase productivity, efficiency, and accuracy which results in huge benefits to the organization. Analytic firms like Deloitte, McKinsey etc. predicted that in the next few years, data science will lead all the engineering domains. AICTE in its ‘Approval Process Handbook’ also emphasized the need to include courses related to data science to be a part of curriculum in all branches and faculty from branches like electronics must learn these new technologies. There is a need to find innovative ways to leverage these technologies which are the fastest gaining technologies in the current market. There is a lack of understanding of the potential benefits of these technologies to solve business problems. Deep insights are required into these technologies to find business solutions. This FDP promises to provide teacher’s hands-on training and industry connect for sharing real life case studies.

Major Course Contents:  

• Introduction to Data science and Machine Learning
• Various applications of Data science and Machine Learning
• Installation of Python
• Introduction to Jupyter Notebook
• Hands-on discussion on basic python libraries (such as Numpy, Pandas, Matplotlib etc.)
• Introduction to various Machine Learning Algorithms
• Decision Tree
• Naïve Bayes
• KNN, K-means
• Neural Network
• Implementation of ML algorithm using different Python Library
• Introduction to Convolution Neural Network
• Introduction to Deep Learning
• Hands on Deep Learning models including Convolution Neural Network

Course outcomes of FDP on Data Science are:

• Participants will develop relevant programming abilities.
• Participants will demonstrate proficiency with statistical analysis of data.
• Participants will develop the ability to build and assess data-based models.
• Participants will execute statistical analysis with professional statistical software.
• Participants will demonstrate skills in various tools used for data science.
• Participants will apply data science concepts and methods to solve problems in real-world context and will communicate these solutions effectively.