Last Updated on October 7, 2023 by GeeksGod
Course : Python Numpy Data Analysis for Data Scientist | AI | ML | DL
Python Numpy Data Analysis for Data Scientist | AI | ML | DL
The Python Numpy Data Analysis for Data Scientist course is designed to equip learners with the necessary skills for data analysis in the fields of artificial intelligence, machine learning, and deep learning.
This course covers an array of topics such as creating/accessing arrays, indexing, and slicing array dimensions, and ndarray object. Learners will also be taught data types, conversion, and array attributes.
The course further delves into broadcasting, array manipulation, joining, splitting, and transposing operations.
Learners will gain insight into Numpy binary operators, bitwise operations, left and right shifts, string functions, mathematical functions, and trigonometric functions.
Additionally, the course covers arithmetic operations, statistical functions, and counting functions. Sorting, view, copy, and the differences among all copy methods are also covered.
By the end of the course, learners will be proficient in using Python Numpy for data analysis, making them ready to take on the challenges of the data science industry.
What you can do with Pandas Python
Data analysis: Pandas is often used in data analysis to perform tasks such as data cleaning, manipulation, and exploration.
Data visualization: Pandas can be used with visualization libraries such as Matplotlib and Seaborn to create visualizations from data.
Machine learning: Pandas is often used in machine learning workflows to preprocess data before training models.
Financial analysis: Pandas is used in finance to analyze and manipulate financial data.
Social media analysis: Pandas can be used to analyze and manipulate social media data.
Scientific computing: Pandas is used in scientific computing to manipulate and analyze large amounts of data.
Business intelligence: Pandas can be used in business intelligence to analyze and manipulate data for decision-making.
Web scraping: Pandas can be used in web scraping to extract data from web pages and analyze it.
Instructor: Faisal Zamir
Faisal Zamir is an experienced programmer and an expert in the field of computer science. He holds a Master’s degree in Computer Science and has over 7 years of experience working in schools, colleges, and university.
As a programmer, Faisal has worked on various projects and has experience in multiple programming languages, including PHP, Java, and Python. He has also worked on projects involving web development, software engineering, and database management.
As an instructor, Faisal has a proven track record of success. He has taught students of all levels, from beginners to advanced, and has a passion for helping students achieve their goals.
Course Outline: Python Numpy Data Analysis for Data Scientist
These are the outlines that will be covered in the course:
Introduction to Numpy
Numpy Environment Setup
Indexing & Slicing
Array dimensions (1, 2, 3, ..N)
Data type Conversion
Array ndarray object attributes
Array creation in different ways
Array from existed data
Array from ranges function
Update Array values
Array Manipulation Operations
Array Joining Operations
Array Transpose Operations
Array Splitting Operations
Array More Operations
Numpy binary operators – Binary Operations
The difference among all copies method
30-day Money-Back Guarantee
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This means that if you are not satisfied with the course within the first 30 days of purchase, you can request a full refund.
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So if you’re looking to improve your skills in Python data analysis for data science, AI, ML, or DL, this course is definitely worth considering.
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In today’s data-driven world, data analysis skills are in high demand. By learning Python Numpy, you’ll be equipped to tackle complex data analysis tasks, whether in the field of artificial intelligence, machine learning, or deep learning.
With our comprehensive Python Numpy Data Analysis course, you’ll learn the fundamentals of data analysis, including creating and accessing arrays, indexing, slicing array dimensions, and working with the ndarray object. You’ll also gain an understanding of data types, conversions, and array attributes.
In addition, our course covers advanced topics such as broadcasting, array manipulation, joining, splitting, and transposing operations. You’ll also explore Numpy binary operators, bitwise operations, string functions, mathematical functions, and trigonometric functions.
We understand that hands-on practice is crucial in learning data analysis. That’s why our course provides numerous coding exercises and real-world examples to reinforce your understanding. By the end of the course, you’ll be proficient in using Python Numpy and ready to tackle data analysis challenges in your career.
Don’t miss out on this opportunity to enhance your data analysis skills and boost your career prospects. Enroll in our Python Numpy Data Analysis course today with a Free Udemy Coupon!