This webinar will introduce you to the fundamental concepts of data science and artificial intelligence, demonstrating how Python can be used to extract, explore, and analyze data to drive better business decisions. Join us to learn how to harness the power of data to increase revenue, improve operational efficiency, and gain a competitive edge.
Complete and submit the form below to register for the webinar.
Python for Data Science and AI Webinar FAQs
This webinar is ideal for:
- Business Professionals: Looking to leverage data science and AI to enhance decision-making processes.
- Aspiring Data Scientists and Analysts: Seeking practical knowledge and hands-on experience with Python.
- IT Professionals: Wanting to integrate data science solutions into existing infrastructure.
- Managers and Executives: Interested in understanding the potential of AI-driven insights to improve business operations.
- Academics and Researchers: Exploring the latest trends and applications in data science and AI.
- Learn about the importance of data science initiatives and how AI is transforming various industries.
- Learn how you can gain practical skills in using Python for data fetching, exploration, and visualization.
- Learn about essential Python libraries such as Matplotlib, Seaborn, Geopandas, Plotly, and Dash for effective data visualization.
- Understand different machine learning techniques and when to use them.
- Learn how evaluating models based on prediction quality, resource requirements, and ethical considerations can help you.
- See how data science and AI solutions are applied in business scenarios to solve problems and generate insights.
Develop the skills to help your organization achieve its strategic objectives:
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Learn more about our Artificial Intelligence Training and Talent Solutions
Chris Mawata
Chris has over 30 years of IT experience, including 17 years of teaching at the university level, and 15 years of training Java and Big Data programmers. As a Learning Tree instructor, Chris has authored four courses. As a consultant, he runs a 20-node cluster on which he has several Big Data frameworks installed. He has published peer-reviewed papers in image processing, artificial intelligence, and pure mathematics.