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Complete Python Numpy Data Analysis Course

6.5 hours
All Levels

Complete Python Numpy Data Analysis Course In this comprehensive NumPy …

What you'll learn
Understand core NumPy concepts, including arrays, data types, and array operations.
Create NumPy arrays using techniques like array literals, ranges, and random number generation.
Explore array manipulation, including reshaping, slicing, and indexing for efficient data extraction and modification.
Master a wide range of mathematical operations in NumPy, including element-wise operations, linear algebra, and statistical functions.
Learn data aggregation with NumPy functions for mean, median, sum, and more.
Grasp the concept of broadcasting and how NumPy handles operations on arrays with different shapes.
Work with masked arrays to gracefully handle missing or invalid data.
Discover integration techniques with other Python libraries, such as pandas for data manipulation and matplotlib for data visualization.
Harness the efficiency of NumPy in handling large datasets and performing vectorized operations.
Acquire best practices for data manipulation, optimization, and maintaining code readability in NumPy.
Explore practical NumPy applications in data analysis, scientific computing, and machine learning.
Develop problem-solving skills by applying NumPy to various data-related challenges and exercises.
Optimize NumPy code for enhanced performance and efficiency.
Learn data transformation and preprocessing techniques critical for data scientists and engineers.
Apply your knowledge through hands-on projects and exercises that reinforce your understanding of NumPy's capabilities.

Exploring Data Science: Comprehensive Pandas Course for Data Analysis and Visualization

111 Lessons
10.7 hours
All Levels

Exploring Data Science: Comprehensive Pandas Course for Data Analysis and …

What you'll learn
Understand the fundamentals of Pandas, its importance in data analysis, and the wide range of tasks it can accomplish.
Install Pandas and execute basic programs to perform data analysis.
Familiarize themselves with different data structures in Pandas, such as Series, DataFrame, and Panel.
Apply descriptive statistics methods and inferential statistics functions for data analysis.
Utilize various function application techniques, including element-wise, row or column-wise, and table-wise operations.
Master reindexing, iteration, and sorting techniques to manipulate and organize data effectively.
Explore the rich set of string methods available in Pandas for text data processing and manipulation.
Customize display options, data types, and data cleaning/manipulation processes according to specific requirements.
Learn indexing and selecting techniques using label-based or integer-based indexing, boolean indexing, and string-based querying.
Perform window functions such as rolling, expanding, and exponentially weighted moving average (ewm) for data analysis.
Understand the concept of grouping data, apply aggregation functions, and filter and transform data based on groups.
Handle categorical data using various methods, including type conversion, value counting, reordering categories, and handling missing categories.
Visualize data using line plots, bar plots, histograms, scatter plots, box plots, area plots, heatmaps, and density plots.
Master I/O tools for reading and writing data in different formats such as CSV, Excel, and JSON.
Explore sparse data features and learn to handle and analyze data with missing values efficiently.

Complete MySQLi Course with Certificate

45 Lessons
4.1 hours
All Levels

Complete MySQLi Course MySQLi is a PHP extension used for …

What you'll learn
Introduction to MySQL, PHP API, MySQL vs MySQLi
Setup & Installation, Website, and Database
Creating a MySQL Database, Connecting to MySQL Database
What is Query (INSERT, SELECT, Update, Delete)
Where Clause (IN & NOT IN BETWEEN, All Operators
LIKE, AND, OR, NOT Operator
LIMIT Clause, MAX Function, MIN Function
Count Function, SUM Function, AVG Function
Export and IMPORT Database
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