Pasigodla Rajiv Shekar Yadav

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Fees

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Generative AI Classes

1

Teaching Experience in detail in Generative AI Classes

I have experience teaching Generative AI concepts to students and professionals, focusing on both theoretical understanding and practical implementation. My teaching covers Large Language Models (LLMs), Prompt Engineering, AI-powered content generation, AI Agents, Retrieval-Augmented Generation (RAG), AI Automation workflows, and real-world business applications of Generative AI. I design structured learning programs that help learners progress from foundational AI concepts to advanced implementation. Topics include understanding transformer-based models, effective prompt design, working with leading AI platforms such as ChatGPT and Claude, integrating AI APIs, building AI-powered applications, and automating workflows using tools such as n8n, Make, and Zapier. My teaching approach emphasizes hands-on learning through projects and case studies. Learners work on practical assignments such as creating AI chatbots, building AI agents, developing content-generation systems, implementing document-question-answering solutions, and automating business processes with Generative AI tools. I also guide students on AI ethics, responsible AI usage, model limitations, data privacy considerations, and emerging industry trends. The objective is to equip learners with job-ready skills that enable them to effectively use and implement Generative AI technologies in professional environments.

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Teaching Experience in detail in Data Science Classes

I have experience teaching Data Science to students and aspiring professionals, covering the complete data science lifecycle from data collection and preprocessing to analysis, visualization, machine learning, and business decision-making. My teaching focuses on building strong analytical thinking and practical problem-solving skills through real-world datasets and industry-oriented projects. The curriculum I deliver includes Statistics, Probability, Data Analysis, Data Cleaning, Exploratory Data Analysis (EDA), Data Visualization, SQL, Python for Data Science, and Machine Learning fundamentals. Students learn to work with popular libraries and tools such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, Jupyter Notebook, and SQL databases. I guide learners through practical applications of data science, including predictive analytics, customer segmentation, classification, regression, recommendation systems, and business intelligence reporting. The training emphasizes hands-on project development, enabling students to analyze datasets, extract insights, create visual dashboards, and build machine learning models. In addition to technical skills, I teach best practices in data preparation, model evaluation, feature engineering, data storytelling, and ethical use of data. Students are encouraged to work on industry-relevant case studies that simulate real-world business challenges and help them develop portfolio-ready projects. My teaching methodology combines conceptual explanations, live demonstrations, guided exercises, assignments, and capstone projects to ensure learners gain both theoretical understanding and practical experience required for data-driven roles in today's industry.