Generative AI with Large Language Models
This is the first comprehensive Coursera course focused on LLMs that details the typical generative AI project lifecycle, including scoping the problem, choosing an LLM, adapting the LLM to your domain, optimizing the model for deployment, and integrating into business applications.
Advantage of this course
- Versatility in job roles
- Data manipulation
- Transferable skills
- Hign Demand
- Actionable insights
- Adaptability
About The Course
Data Analysis has been around for a long time. But up until a few years ago, developers practiced it using expensive, closed-source tools like Tableau. But recently, Python, SQL, and other open libraries have changed Data Analysis forever. In the Data Analysis with Python Certification, you’ll learn the fundamentals of data analysis with Python. By the end of this certification, you’ll know how to read data from sources like CSVs and SQL, and how to use libraries like Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data.
What Will You Learn
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You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn.
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You will learn how to use the pandas library, one of the most powerful tools for data manipulation in Python.
- This knowledge helps you assess the effectiveness of models and select the best ones for deployment.
- The course will start with an introduction to Python programming, covering the basics of variables, data types, control flow, functions, and object-oriented programming (OOP) concepts.
- This practical experience allows you to work with real-world datasets, tackle data analysis problems, and gain confidence in applying your knowledge.
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Course Contents
Introduction to Data Analysis
Data Manipulation with pandas
Statistical Analysis with NumPy and SciPy
FAQ
While prior knowledge of data analytics is not always required, having basic mathematical skills and familiarity with computer applications can be beneficial. Some courses are designed for beginners and assume no prior experience.
Yes, most data analytics courses include real-world projects and case studies where you can apply your learned skills to practical scenarios using real datasets.
Yes, responsible data handling and ethical considerations are often covered, highlighting the importance of data privacy and security.
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