NumPy, Pandas, & Python for Data Analysis: A Complete Guide
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Unlock the full potential of data analysis with NumPy, Pandas, and Python in this comprehensive, hands-on course! Whether you’re a beginner or looking to sharpen your skills, this course will guide you through everything you need to master data analysis using Python’s most powerful libraries.
You will learn to:
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Python for Data Analysis: Master the fundamentals of Python, the most popular language for data science, including core programming concepts and essential libraries.
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NumPy Essentials: Dive deep into NumPy for fast numerical computations, array manipulation, and performance optimization.
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Pandas Mastery: Learn how to efficiently work with large datasets using Pandas, the powerful data manipulation library. Handle, clean, transform, and analyze real-world data with ease.
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Data Visualization: Understand how to represent your data visually to gain insights using Python libraries like Matplotlib and Seaborn.
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Real-World Projects: Apply your knowledge to real-world datasets, tackling data challenges from start to finish—exploring, cleaning, and drawing insights.
What you’ll learn:
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Fundamentals of Python programming for data analysis
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Introduction to NumPy: Arrays, operations, and performance techniques
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Deep dive into Pandas: DataFrames, Series, and advanced data manipulation
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Data cleaning and preprocessing techniques
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Exploratory data analysis (EDA) with Pandas
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Real-world case studies and hands-on projects
Enroll today and take the first step toward mastering data analysis with Python, NumPy, and Pandas!
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3Creating NumPy arrays from Python listsVideo lesson
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4Array indexing, slicing, and reshapingVideo lesson
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5Basic operations with NumPy arraysVideo lesson
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6Mathematical functions in NumPyVideo lesson
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7Working with multidimensional arraysVideo lesson
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8Random number generationVideo lesson
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9Reading and writing files with NumPyVideo lesson
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10Creating and understanding DataFramesVideo lesson
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11Importing and exporting data (CSV, Excel, JSON)Video lesson
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12DataFrame indexing and selectionVideo lesson
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13Adding, removing, and updating dataVideo lesson
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14Handling missing dataVideo lesson
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15Data filtering, sorting, and groupingVideo lesson
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16Understanding time series dataVideo lesson
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17Working with dates and times in PandasVideo lesson
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18Time series analysis and manipulationVideo lesson
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