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The Complete Python Data Science & Machine Learning Bootcamp is …
What you'll learn
Python programming fundamentals and best practices for data science
Data handling and manipulation using NumPy and Pandas
Data visualization using Matplotlib and Seaborn
Exploratory Data Analysis (EDA) to discover patterns and insights
Data cleaning, handling missing values, and outlier treatment
Statistical concepts including probability, distributions, and hypothesis testing
Feature engineering techniques such as scaling, encoding, and binning
Machine learning algorithms and their practical applications
Model evaluation and performance improvement techniques
Building and deploying machine learning projects using Flask and AWS
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Python Programming For Everyone: Learn From Basics to Advanced
Python Programming for Everyone: Learn Basics to Advanced is a …
What you'll learn
Understand Python fundamentals, syntax, and programming best practices.
Write programs using variables, data types, input/output, and strings.
Apply conditional statements and loops to solve logical problems.
Work confidently with Python data structures: lists, tuples, sets, and dictionaries.
Use functions effectively, including arguments, return values, and scope.
Handle errors and exceptions using try, except, else, and finally.
Implement object-oriented programming concepts such as inheritance and polymorphism.
Perform numerical computing and data manipulation using NumPy and Pandas.
Clean, filter, and engineer features from real-world datasets.
Create insightful data visualizations using Matplotlib and Seaborn.
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Python Programming for Data Analytics: Learn Basics to Advanced
Why Purchase “Python Programming for Data Analytics: Learn Basics to …
What you'll learn
Learn complete Python fundamentals, including variables, loops, functions, and file handling.
Understand and apply Python data structures such as lists, tuples, sets, and dictionaries.
Build strong programming skills with Object-Oriented Programming (OOPS).
Perform data analysis using industry-standard libraries like NumPy and Pandas.
Create professional charts and graphs using Matplotlib and Seaborn for data visualization.
Develop real-world problem-solving and debugging skills to write clean, efficient code.
