Welcome
IPN-Dharma AI Lab
This is an IPN CIC - DHARMA initiative to provide an Artificial Intelligence Laboratory to motivate researchers, professors and students to take advantage of the courses, resources and tools of the main technology platforms of the industry in the areas of Machine Learning, Data Science, Cloud Computing, Artificial Intelligence and Internet of Things with the purpose of generating a practical experience through a learning model between peers and by objectives.
Level 1: Literacy and Foundations
Data Science Foundations
This is a four-course program that provides foundational skills to start a career in data science. It introduces what data science is and what data scientists do, the applicability of data science, and how data analytics can help make data-driven decisions.
The concepts of Big Data, statistical analysis and relational databases, and several open source tools such as Jupyter Notebooks, RStudio, and SQL are shown. Hands-on labs and projects are conducted to learn the methodology involved in tackling data science problems and apply newly acquired skills and knowledge to real-world data sets.
The concepts of Big Data, statistical analysis and relational databases, and several open source tools such as Jupyter Notebooks, RStudio, and SQL are shown. Hands-on labs and projects are conducted to learn the methodology involved in tackling data science problems and apply newly acquired skills and knowledge to real-world data sets.
Courses in this program
1) Introduction to Data Science
People who work in data science have created a unique and distinct field for the work they do. This field is data science, and in this course, you will meet some data science professionals who deal with large amounts of data (Big Data) and get an overview of what data science is today.
Estimated effort 3 hours
Spanish & English language
2) Data Science Tools
In this course you will learn about data science tools such as Jupyter Notebooks, RStudio IDE and Watson Studio. You'll learn what each tool is used for, what programming languages they can run, their features and limitations, and how data scientists use these tools today.
With the tools hosted in the cloud, you will be able to use each tool and follow instructions to execute simple code in Python or R. To complete the course, you will create a final project in the cloud with a Jupyter Notebook in IBM Watson Studio, demonstrating your ability to prepare a notebook, write Markdown and share your work.
With the tools hosted in the cloud, you will be able to use each tool and follow instructions to execute simple code in Python or R. To complete the course, you will create a final project in the cloud with a Jupyter Notebook in IBM Watson Studio, demonstrating your ability to prepare a notebook, write Markdown and share your work.
Estimated effort 4 hours
Spanish & English language
3) Data Science Methodology
The purpose of this course is to share the methods, models, and practices that can be applied within data science to ensure that data used in problem solving is relevant and properly manipulated to address real-world and business challenges.
You will learn how to identify a problem, collect and analyze data, build a model, and understand feedback after model deployment.
You will learn how to identify a problem, collect and analyze data, build a model, and understand feedback after model deployment.
Estimated effort 5 hours
Spanish & English language
4) SQL and Relational Databases
Much of the world's data resides in databases. SQL (Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases.
The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment.
The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment.
Estimated effort 6 hours
Spanish & English language