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 2: Contextual Knowledge
Data Science Professional
Data science and machine learning skills continue to be in high demand across industries, and the need for data professionals is booming.
In this program, through practical tasks you will create a portfolio using real data science tools with real-world datasets and problems. The curriculum will cover a wide range of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analytics, and machine learning.
No previous knowledge of computer science or programming is required to be able to take this program. This program is a continuation of the Data Science Foundations program, so it is recommended to have taken it before taking this program.
Courses in this program
1) Python for Data Science and AI
This is an introductory Python course for artificial intelligence, data science, and general programming that will quickly take you from scratch to programming in Python in a matter of hours and give you an idea of how to start working with data in Python.
Upon completion, you will be able to write your own Python scripts and perform basic hands-on data analysis using our Jupyter-based lab environment. You'll also be able to create your own data science projects and collaborate with other data scientists using IBM Watson Studio.
Upon completion, you will be able to write your own Python scripts and perform basic hands-on data analysis using our Jupyter-based lab environment. You'll also be able to create your own data science projects and collaborate with other data scientists using IBM Watson Studio.
Estimated effort 5 hours
Spanish & English language
2) Data Analysis with Python
In this data science course, you will learn how to use the Python language to clean, analyze, and visualize data. You'll learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, and predict future trends from data with hands-on labs.
Estimated effort 8 hours
Spanish & English language
3) Data Visualization with Python
Data visualization plays an essential role in the representation of data both on a small and large scale. One of the key skills of a data scientist is the ability to tell a compelling story, visualize data and insights in an accessible and thought-provoking way.
In this course, we will use various data visualization libraries in Python, Matplotlib, Seaborn and Folium, which will allow you to extract information, better understand the data and make more effective decisions. You can also start creating your own data science projects and collaborate with other data scientists using IBM Watson Studio.
In this course, we will use various data visualization libraries in Python, Matplotlib, Seaborn and Folium, which will allow you to extract information, better understand the data and make more effective decisions. You can also start creating your own data science projects and collaborate with other data scientists using IBM Watson Studio.
Estimated effort 10 hours
Spanish & English language
4) Machine Learning with Python
This machine learning with Python course dives into the basics of machine learning using a familiar and accessible programming language. You will learn about supervised and unsupervised learning, see how statistical modeling is related to machine learning, and compare each.
Explore many algorithms and models:
Explore many algorithms and models:
- Algorithms: Classification, Regression, Clustering and Dimensional Reduction.
- Models: Train/Test Split, Root Mean Squared Error and Random Forests.
Estimated effort 12 hours
Spanish & English language
5) Applied Data Science Capstone
This capstone project course will give you a taste of what data scientists go through in real life when working with real datasets, by the end you will have used real world data science tools.
Estimated effort 24 hours
Spanish & English language