Updating _toc.yml

docs/course-requirements/learning-python.md

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-# Python Environment Configuration
-In this section, we provide the minimal Python packages required to complete the programming exercises in this course. We are saying minimal because for some of the project work, you may need extra packages
+# Essential Python Foundations and Learning Resources 
+To build effective and efficient applications with language models, a solid foundation in Python is essential. This section outlines the core Python skills that will support your development journey, from basic programming principles to essential tools for working with APIs and managing environments. Additionally, a curated list of free resources is provided to help you either learn or review these skills, ensuring you have the confidence and capability to maximize your work with language-based applications.
 
 ## Prerequisite Python Skills
 A solid foundation in core Python skills is essential for building LLM-based applications with LangChain. These prerequisites enable efficient coding, debugging, and API interaction, which are critical for working effectively with language models. Below is a list of recommended skills to help you maximize your learning in this course.

docs/malawi-nov-24/malawi.md

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-# LLM Application Development with LangChain and Python
+# Session Overview 
+> Course title: LLM Application Development with LangChain and Python
 In this iteration of the course, participants will explore how to develop advanced applications using Large Language Models (LLMs) with the LangChain framework in Python. Through practical exercises and real-world case studies, the course dives into the technical aspects of building LLM-powered solutions, covering everything from prompt engineering to integrating various data sources and APIs. Participants will gain hands-on experience in creating dynamic applications, including intelligent chatbots and automated workflows. The course begins by providing a foundational understanding of LLMs—how they are trained and adapted for different domains through techniques like prompt engineering and fine-tuning. It then introduces LangChain, a leading framework for building LLM applications, empowering participants to enhance their business processes with LLMs. Ideal for developers, data scientists, data engineers, analysts, and professionals across industries such as banking, telecommunications, and the public sector, this course equips you with the skills needed to build your first production-grade LLM application.
 
 The course is structured into self-contained modules, each building on the skills learned in previous ones. Each module includes lectures for key concepts, practical labs with programming activities and modifiable recipes, and case studies that showcase real-world applications. To reinforce learning, assessments combine theoretical and programming questions to evaluate the learner's understanding and skills gained.
 
-
-
 ## Session Details
 
 ### Audience

notebooks/malawi-nov-24/mw-notebooks-intro.md

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-# Programming Activities for the Course
+# Programming Activities
 
 This document outlines the programming activities for the course, focusing on hands-on projects to apply the concepts learned. The document is organized into two main sections: an introduction to LLM capabilities and LangChain, followed by a practical exercise on deploying a chatbot with Streamlit.