Certifications

This certification enhances Python programming skills through comprehensive training, optimizing code using built-in modules and functions. Gain hands-on experience in writing well-documented functions and utilizing context managers, decorators, and popular Python packages. Develop proficiency in software engineering concepts, automated testing, and object-oriented programming (OOP) principles for code maintainability.

This program aims to supercharge data science skills through Python data visualization. Explore Matplotlib, Seaborn, Bokeh, and more libraries for creating static and interactive visualizations. Develop skills to showcase data effectively and confidently create Python visualizations. Applicable across industries, data visualization tells impactful stories with data.

This program intends to develop vital data preparation skills in Python to uncover insights. Import diverse data sources (.csv, .xls, text files) and ready them for analysis. Handle data types, missing values, and perform record linkage with real-world datasets. Utilize Tweepy for web scraping and accessing Twitter’s API.

This course is designed to teach you the foundations in order to write simple programs in Python using the most common structures. By the end of this course, you’ll understand the benefits of programming in IT roles; be able to write simple programs using Python; figure out how the building blocks of programming fit together; and combine all of this knowledge to solve a complex programming problem.

This program is intended to equip its learner with foundational Python skills for data science. Learn data cleaning, visualization, and function writing. Instructor Hugo highlights Python’s business applications. Hands-on exercises cover NumPy, Matplotlib, and pandas.

Learn Shiny, use R to build interactive web apps. Share analyses as dashboards and visualizations. Explore Gapminder, Star Wars, and NASA datasets with explorable visualizations. Improve insights and communicate visually. Elevate data visualization skills.

Acquire career-building R skills for data analysis success. NoAcquire career-building R skills for data analysis success. No prior coding experience required. Learn data import, cleaning, manipulation, and visualization in R. Hands-on experience with popular packages like ggplot2, tidyverse, dplyr, and readr. Develop data manipulation and exploratory analysis skills using real-world datasets. Gain statistical expertise for hypothesis testing.