Conversation Code II

Goals

This training aims to develop core AI knowledge by leveraging Python's toolset, focusing on conversational English and using an adapted Agile methodology called JACI - Just, Autodidact, Collaborative and Intense. We'll be studying Python first, going through the basics and the necessary toolset in order to prepare for the AI course.

Planning

• Start day: 30/10/2023
• End day 10/03/2024
• Link to channel meetings:
• Hours of dedication: 2hours a day

Agile Methodology

We will modify the Agile methodology to enhance the management of our training. In this scenario, we will incorporate sprints to determine the specific topics we will be studying over a two-week period. Alongside the sprints, we will conduct Daily meetings once a week to facilitate efficient communication among team members, ensure progress updates, identify potential obstacles, and foster collaboration. Along this we still have a Sprint Planning that is a meeting with all the members that defines which chapter will fit in which sprint. At the end of each sprint, we will do a review for evaluations and revisions of the work sequence.

• Scrum:
  • Scrum Master: Clara Conhalato Simão
  • Sprints: two-week period
  • Daily: once a week
  • Sprint Planning: defines which chapter will fit in which sprint

J.A.C.I. Method

• Meanig:
  • Just: Adapts to the level of each participant.
  • Autodidact: Material for reading and use the chat group to debate
  • Collaborative: The main goal of this project is to help each other learn more about programming by sharing your knowledge.
  • Intense: Since day one the students have exercises and a final project.

Material

• Alura:
• YouTube videos:

• Exercises

• Final Project
  • AI
  • Python

• Schedule

Team

1. Clara Conhalato Simão
2. Marcus Vinícius Torres Silva
3. Ingrid Lima Cro Rossi
4. Gabriel Carneiro Marques Amado
5. Amanda Varnier Massarioli de Oliveira
6. Guilherme Almeida Andrade
7. Gessyca Carneiro Bernardes
8. Vinícius Araujo
9. Ana Lídia Costa Nunes

Python

(Write here why we should study python)

AI with Data Science

Data science uses AI (and its subset, Machine Learning) to interpret historical data, recognize patterns, and make predictions. In this case, AI and Machine Learning assist data scientists in gathering data in the form of insights.

As mentioned, Machine Learning is a branch of AI, advancing data science to the next level of automation. Machine Learning algorithms are trained on data provided by data science to become smarter and more informed when making predictions. Therefore, Machine Learning algorithms rely on data, as they won't learn without using them as a training set.

Team in charge

1. Gessyca Carneiro Bernardes(AI instructor)
2. Gabriel Carneiro Marques Amado (Python instructor)
3. Clara Conhalato Simão (English instructor)