Data Science in Action using Python & LLM (Self-Paced)
Master Advanced Data Science Techniques Using Python and Generative AI
 
👉 Start learning today and gain a competitive edge in AI!
 
Course Overview
Embark on a journey through the evolution of data science with "Data Science in Action using Python and Generative AI." This self-paced course explores the transition from Business Intelligence (BI), popularized in the 1990s, to today’s cutting-edge AI-driven data analytics.
In the era of big data, the challenges of handling large volumes of high-velocity information and diverse data types (including speech, text, and video) require more advanced solutions. This course demonstrates how traditional BI methodologies have adapted to the demands of modern AI and machine learning.
Through real-world case studies and hands-on exercises, you’ll explore how to apply data science techniques using Python and Scikit-learn — even if you have no prior coding experience. The course introduces a modified CRISP-DM (Cross-Industry Standard Process for Data Mining) framework, tailored to address the complexities of AI and big data.
This course combines technical skills with business insights, equipping you with the tools and knowledge to solve complex data challenges and drive strategic business decisions using AI-driven data science.
 
Key Learning Objectives
By the end of this course, you will be able to:
✅ Understand the evolution of data science – Explore the shift from traditional business intelligence to AI-driven data analytics.
✅ Master big data challenges – Learn how to manage large volumes of high-velocity, unstructured data, including speech, text, and video.
✅ Apply the modified CRISP-DM methodology – Develop AI and data science models using a refined framework tailored for big data.
✅ Develop practical solutions using Python and Scikit-learn – Gain hands-on experience with Python for data analysis and modeling.
✅ Solve real-world business challenges – Apply your knowledge to real-life case studies and create prototypes for data science projects.
✅ Integrate AI and data science techniques – Leverage Generative AI and machine learning to uncover actionable business insights.
 
Who Should Attend
This course is ideal for:
✔️ Aspiring data scientists looking to build practical AI-driven solutions.
✔️ Business analysts and consultants working with large-scale data.
✔️ AI developers and IT professionals seeking to enhance their data science skills.
✔️ Data and business intelligence professionals adapting to AI-driven processes.
✔️ Product managers and strategists using data for decision-making.
 
Prerequisites
To enroll in this course, you should have:
Basic understanding of data analysis concepts.
No prior Python experience required — the course includes step-by-step Python instruction.
An analytical mindset and a willingness to learn.
 
Expected Outcome
Upon successful completion of the course, you will:
✅ Gain a deep understanding of data science evolution and AI-driven analytics.
✅ Be able to handle large-scale, high-velocity data across multiple formats.
✅ Develop AI models using Python and Scikit-learn.
✅ Apply the modified CRISP-DM methodology to real-world business scenarios.
✅ Design and prototype data science projects to solve business challenges.
✅ Earn a recognized certification in Data Science from the Applied AI Institute (AAII).