Advanced Data Mastery

• Understanding the importance of data management in various domains.
• Exploring different free and open-source tools available for data management.
• Learning how to use these tools for data collection, storage, organization, analysis, and visualization.
• Implementing best practices for efficient data management using these tools.
• Applying their knowledge to real-world scenarios and projects.
• Understanding the importance of data visualization in data analysis and decision-making.
• Exploring different data visualization techniques and tools for various types of data.
• Learning automation strategies to streamline data-related tasks and workflows.
• Implementing automation tools and techniques to increase productivity and efficiency.
• Applying data visualization and automation strategies to real-world scenarios and projects.

• Understand the importance of effective data management in various contexts.
• Identify suitable free and open-source tools for different aspects of data management.
• Utilize tools for data collection, storage, organization, analysis, and visualization effectively.
• Implement best practices for efficient data management, including data cleaning, security, and documentation.
• Apply their knowledge and skills to real-world data management tasks and projects.
• Analyze data effectively and present insights using appropriate visualization techniques.
• Collaborate with others using version control and documentation practices.
• Continuously improve their data management skills through self-learning and exploration of new tools and techniques.
• Understand the importance of data visualization and automation in data analysis and decision-making.
• Choose appropriate data visualization techniques and tools for different types of data.
• Utilize data visualization tools effectively to create insightful and interactive visualizations.
• Implement automation strategies to streamline data-related tasks and workflows.
• Apply automation tools and techniques to increase productivity and efficiency in data management.
• Integrate data visualization and automation to create automated reporting systems and dashboards.
• Implement best practices for effective data visualization design and automation implementation.
• Analyze real-world data scenarios and apply data visualization and automation strategies to solve problems and make informed decisions.

The academic approach of the courses focuses on the “work-centric” education i.e. begin with work (and not from a book!), derive knowledge from work and apply that knowledge to make the work more wholesome, useful and delightful. The ultimate objective is to empower the Learner to engage in socially useful and productive work. It aims at leading the learner to his/her rewarding career as an employee or entrepreneur as well as development of the community to which s/he belongs. Learning methodology:

• Step -1: Learners are given an overview of the course and its connection to life and work.
• Step -2: Learners are exposed to the specific tool(s) used in the course through the various real-life applications of the tool(s).
• Step -3: Learners are acquainted with the careers and the hierarchy of roles they can perform at workplaces after attaining increasing levels of mastery over the tool(s).
• Step -4: Learners are acquainted with the architecture of the tool or tool map so as to appreciate various parts of the tool, their functions, utility and inter-relations.
• Step -5: Learners are exposed to simple application development methodology by using the tool at the beginner’s level.
• Step -6: Learners perform the differential skills related to the use of the tool to improve the given ready-made industry-standard outputs.
• Step -7: Learners are engaged in appreciation of real-life case studies developed by the experts.
• Step -8: Learners are encouraged to proceed from appreciation to imitation of the experts.
• Step -9: After the imitation experience, they are required to improve the expert’s outputs so that they proceed from mere imitation to emulation.
• Step-10: Emulation is taken a level further from working with differential skills towards the visualization and creation of a complete output according to the requirements provided. (Long Assignments)
• Step-11: Understanding the requirements, communicating one’s own thoughts and presenting are important skills required in facing an interview for securing a work order/job. For instilling these skills, learners are presented with various subject-specific technical as well as HR-oriented questions and encouraged to answer them.
• Step-12: Finally, they develop the integral skills involving optimal methods and best practices to produce useful outputs right from scratch, publish them in their ePortfolio and thereby proceed from emulation to self-expression, from self-expression to self-confidence and from self-confidence to self-reliance and self-esteem!

Evaluation Pattern of KLiC Courses consists of 4 Sections as per below table:

YCMOU Mark Sheet

Printed Mark Sheet will be issued by YCMOU on successful completion of Section 1, Section 2 and Section 3 and will be delivered to the learner by MKCL.
YCMOU Mark Sheet will be available only for Maharashtra jurisdiction learners

MKCL's KLiC Certificate

The certificate will be provided to the learner who will satisfy the below criteria:

1. Learners who have successfully completed above mentioned 3 Sections i.e. Section 1, Section 2 and Section 3
2. Additionally, learner should have completed Section 4 (i.e. Section 4 will comprise of SUPWs i.e. Socially Useful and Productive Work in form of Assignments)
   • Learner has to complete and upload minimum 2 out of 5 Assignments