About the Course
We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning:
Programming with Python
NumPy with Python
Using pandas Data Frames to solve complex tasks
Use pandas to handle Excel Files
Web scraping with python
Connect Python to SQL
Use matplotlib and seaborn for data visualizations
Use plotly for interactive visualizations
Machine Learning with SciKit Learn, including:
K Nearest Neighbors
K Means Clustering
Natural Language Processing
Neural Nets and Deep Learning
Support Vector Machines
and much, much more!
Enroll in the course and become a data scientist today!
Makanjuola is a 2nd-year Computer Science Ph.D. Student at Virginia Tech, and a member of the Sanghani Center for Artificial Intelligence & Data Analytics. He is conducting research on Emergent Communication, in particular multi-modal, multi-agent communication where he models AI agents to collaborate and invent efficient communication strategies for task completion and to come up with intelligence that imitates and approximates human intelligence.
He has a broad interest in the field of Data Analytics, Data Science, Machine Learning, Natural Language Processing, Computational Linguistics, and Digital Humanities. Makanjuola has a notable understanding of data structures and algorithms, especially in the python programming language, and has been fortunate to be a two-time co-facilitator of the Deeper Life Young Adult - Dallas Region Bootcamp!
Mr. Thomas Torku is a talented mathematics educator with focus on student success and empowers students of different ability levels to excel in math. He is a Ph.D. computational science candidate at Middle Tennessee State University (MTSU-USA) who deploys numerical analysis, machine learning and deep learning in epidemiology research and stochastic differential equations.
Due to this passion for real application of data science, Mr. Torku is currently working for JPMorgan Chase & Co. as Quantitative Analyst Summer Associate Intern. He makes use of popular data science libraries such as NumPy, pandas, TensorFlow, Pytorch, Pyspark etc. to draw insights from data-driven models.
With his expertise in applied mathematics and data science, Mr. Torku hopes to impact knowledge, skills and understanding of the real-world applications of data science.