Gian Jyoti Institute of Management & Technology (GJIMT) successfully hosted an in-depth Workshop on Data Sciences Using R on September 9, 2019. The workshop, designed to enhance data science capabilities, took place in the GJIMT Conference Room, with 23 faculty members participating. Spearheaded by Dr. Aneet Bedi, Director, GJIMT, and coordinated by Ms. Silky, the program aimed to provide a robust understanding of R programming and advanced data manipulation techniques.
The workshop featured three sessions led by expert faculty members, offering participants both theoretical knowledge and hands-on experience:
Session 1 – Led by Prof. Gurdeep Singh , Prof. Singh introduced participants to the fundamentals of R programming, covering data types, importing data, and essential data handling operations. His session laid the groundwork for effective data management, ensuring participants could confidently perform initial data preparation tasks.
Session 2 – Led by Dr. Neeraj Sharma , Dr. Sharma delved into advanced data transformation and summarization using the DPLYR package. He emphasized the importance of reproducibility in data science and demonstrated how to create reproducible reports with Markdown, providing valuable insights into documentation best practices.
Session 3 – Led by Mr. Vivek, The final session focused on predictive modeling, data visualization, and model comparison. Mr. Vivek showcased the practical application of the Modelr and BROOM packages, guiding participants through model evaluation and iterative improvements using the Purr package.
The workshop was a resounding success, achieving its goal of equipping participants with practical data science skills. Prof. Gurdeep Singh, Dr. Neeraj Sharma, and Mr. Vivek provided valuable expertise, ensuring participants left with a deeper understanding of data science practices and R programming tools.
This event reflects GJIMT’s commitment to providing cutting-edge knowledge and hands-on learning experiences, preparing participants to excel in the evolving field of data science.