CBT Nuggets | Python For Data Analysts [FCO]

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size3.5 GB
  • Uploaded BySunRiseZone
  • Downloads166
  • Last checkedMay. 27th '22
  • Date uploadedMay. 25th '22
  • Seeders 14
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CBT Nuggets - Python For Data Analysts [FCO]



Author : Jonathan Barrios
Language : English
Released : 2022
Duration : 5h 57m
Course Source : https://www.cbtnuggets.com/it-training/data-science/intro-python-data-analysis

Description

This entry-level Python for Data Analysts training prepares learners to master what is easily the best programming language in the world for data analysis: Python and its data analysis libraries.

Good data analysis makes sense of the past, guides present action and can even predict the future – Python puts all that possibility within reach. And doing data analysis with Python almost always requires a good foundation in Python and comfort in its libraries like Pandas, NumPy and even IPython.

Python is the world's leading programming language for data analysis for a reason: it's versatile, powerful, intuitive, relatively easy, and the open source language has libraries and add-ons that are kept up-to-date by programmers and analysts all over the world. You can learn it and master it for data analysis with this course.

For anyone who manages their Python training, this Python training can be used to onboard new aspiring data analysts, curated into individual or team training plans, or as a Python reference resource.

Python for Data Analysts: What You Need to Know

This Python for Data Analysis training covers Python topics including:

• Analyzing data with Python and Python libraries special made for data analysis
• Identifying and acquiring the right data and types of data with Python
• Performing simple and complex statistical analyses
• Generating data visualizations and creating charts automatically
• Using Python to predict future trends from data

Who Should Take Python for Data Analysts Training?

This Python for Data Analysis training is considered specialist-level Python training, which means it was designed for aspiring data analysts.

New or aspiring data analysts . This course is perfect for someone who just wants to make their everyday job a bit better with data analysis as well as people hoping to start a career as a full-fledged data analyst. Learning Python for data analysis is the key to taking huge sets of data, making sense of them, and making better decisions – and that's useful for anyone.

Experienced aspiring data analysts . If you've been working as a data analyst for a few years already, ask yourself how comfortable you are with Python, Pandas and NumPy. If you're even remotely uncertain about those libraries, why wouldn't you take a course that walks you through using the most powerful and popular data analysis languages and libraries and gives you plenty of chances to practice them?.

About Instructor

Jonathan Barrios- Nugget trainer since 2021

"Helping aspiring data professionals learn about data and seeing them succeed is one of my greatest passions as a trainer. I love to learn, share my knowledge, and help others succeed—this is why I am passionate about being a trainer at CBT Nuggets."

Jonathan started his career as a full-stack developer and quickly became interested in combining his online education experience with his data science and machine learning knowledge. Jonathan has been a programmer, data analytics instructor, and curriculum writer for several leading online education platforms is excited to share his skills and education experience with aspiring data practitioners at CBT Nuggets.

Files:

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  • 1. Python Development Environments.mp4 (47.3 MB)
  • 10. Strings and Keywords.mp4 (48.0 MB)
  • 11. Collections.mp4 (71.3 MB)
  • 12. Code Challenge.mp4 (87.4 MB)
  • 13. Introduction to Python Numbers.mp4 (59.7 MB)
  • 14. Variables.mp4 (92.8 MB)
  • 15. Math Operators.mp4 (104.2 MB)
  • 16. Math with Python.mp4 (107.2 MB)
  • 17. Boolean Values.mp4 (65.3 MB)
  • 18. Code Challenge.mp4 (59.9 MB)
  • 19. Introduction to Strings.mp4 (41.9 MB)
  • 2. Code Editors and IDEs vs. Interactive Notebooks.mp4 (82.5 MB)
  • 20. Working with Strings.mp4 (41.9 MB)
  • 21. Indexing and Slicing Strings.mp4 (103.5 MB)
  • 22. String Methods.mp4 (112.6 MB)
  • 23. Strings Code Challenge.mp4 (69.6 MB)
  • 24. Introduction to Python Functions.mp4 (34.8 MB)
  • 25. Python Operators.mp4 (121.5 MB)
  • 26. Functions and If Statements.mp4 (126.9 MB)
  • 27. Python Scope.mp4 (104.4 MB)
  • 28. Functions Code Challenge.mp4 (83.2 MB)
  • 28. Pseudocode.mp4 (89.5 MB)
  • 3. Installing Google Colab.mp4 (132.3 MB)
  • 30. Introduction to Python Loops.mp4 (64.0 MB)
  • 31. If, elif, and else.mp4 (99.3 MB)
  • 32. For Loops.mp4 (102.5 MB)
  • 33. While Loops.mp4 (112.8 MB)
  • 34. Code Challenge.mp4 (171.5 MB)
  • 35. Introduction to Python Collections.mp4 (43.1 MB)
  • 36. Lists.mp4 (148.5 MB)
  • 37. List Methods.mp4 (163.1 MB)
  • 38. Dictionaries.mp4 (76.9 MB)
  • 39. Dictionary Methods.mp4 (94.2 MB)
  • 4. Installing Jupyter notebook with Anaconda.mp4 (75.4 MB)
  • 40. Code Challenge.mp4 (101.3 MB)
  • 41. Data Analysis Preview with pandas.mp4 (158.5 MB)
  • 5. Managing Projects Environments with Conda.mp4 (49.6 MB)
  • 6. Running Anaconda with Docker.mp4 (64.2 MB)
  • 7. Introduction to Python Data Types.mp4 (65.2 MB)
  • 8. Data Types.mp4 (80.5 MB)
  • 9. Numbers and Bools.mp4 (40.7 MB)

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