About Workshop
This course bridges the gap between introductory and advanced courses in Python. While there are many excellent introductory Python courses available, most typically do not go deep enough for you to apply your Python skills to research projects. In this course, after first reviewing the basics of Python 3, we learn about tools commonly used in research settings. Using a combination of a guided introduction and more independent in-depth exploration, you will get to practice your new Python skills with various case studies chosen for their scientific breadth and their coverage of different Python features. This run of the course includes revised assessments and a new module on machine learning.
This course is ideal for Academicians, Professors, Teachers, B. Tech Students, BCA, MCA, BSc Computer Science, Graduates, Post Graduate and Doctoral (PhD) Students, Researchers and Professionals Working in Government Sector, Project Managers, Research Staff and Coordinators and Data Managers. Post Graduates, Doctoral Scholars and Medical Doctors who are currently working on their dissertation or recently completed their research work and interested to publish their research findings will greatly benefit from this course.
- Computational Thinking and Problem Solving
- Introduction To Python
- Data Types, Expressions, Statements
- Control Flow, Functions, Strings
- Lists, Tuples, Dictionaries
- Files, Modules, Packages
- Illustrative Problems & Programs
- Python Research Tools
- Case Studies
- Statistical Learning
- Python tools (e.g., NumPy and SciPy modules) for research applications
- Python research tools in practical settings
-
At the end of course, participants would have:
- Develop algorithmic solutions to simple computational problems.
- Develop and execute simple Python programs.
- Write simple Python programs using conditionals and loops for solving problems.
- Decompose a Python program into functions.
- Represent compound data using Python lists, tuples, dictionaries etc.
- Read and write data from/to files in Python programs.
- Develop a web page using Django.
-
Participants will earn
- Hands-On Training with Examples
- Certificate from ISO Certified Govt Recognized Research Foundation.
- 24×7 Support from the Experts through WhatsApp or email.
- Placement Assistance..
- Industry Exposure.
About the Resource Persons
Prof. L. A. Anto Gracious has been with the St. Xavier’s Catholic College of Engineering as a Professor in the Department of Computer Science and Engineering. He worked as a software engineer at Sigma college of architecture. His areas of interest include Web Application Development, Cloud Computing, Wireless Sensor Networks and Python Programming. Prof. Anto Gracious has published several research papers in national and international peer reviewed journals. He has given talk in several workshops and conferences.