Python for Data Science by Starweaver

[LeeAndro]

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 59 lectures (9h 5m) | Size: 2.73 GB

Use various analysis and visualization tools associated with Python, such as Matplotlib, Seaborn etc.

An introductory to intermediate level program in Python, and how to apply it in data science

Explain machine learning and its technologies

Discuss and apply Python fundamentals

Understand the NumPy package

Use data analysis using Pandas and data visualization

Implement supervised (regression and classification) & unsupervised (clustering) machine learning

Describe the behavior of data in Python models

Understand how to use the various Python libraries to manipulate data, like Numpy, Pandas and Scikit-Learn

Use Python libraries and work on data manipulation, data preparation and data explorations

Basic Python knowledge is assumed

Some software development experience (including languages, databases...)

This Python for Data Science course is an introduction to Python and how to apply it in data science. The course contains ~60 lectures and 7.5 hours of content taught by Praba Santanakrishnan, a highly experienced data scientist from Microsoft.

Staring with some fundamentals about "what is data science," and "who is a data scientist," the program rapidly move into the specific challenges of data science. This includes the challenges of problem definitions and collecting data, to data pipelines, data preparation, data cleaning and related subjects. Data science methodologies, data analytics tools and open source tools are all covered. Model building validation, visualization and various data science applications are also covered. Discussion of the types of machine learning are covered, including supervised and unsupervised machine learning, as well as methodologies and clustering. NumPy, Pandas, Python Notebook, Git, REPL, IDS and Jupyter Notebook are also covered. Arrays, advanced arrays, and matrices are discussed in some detail to ensure you understand what it is all about and how these tools are implemented.

New Python developers looking to quickly develop and keen understanding of the power of Python

Early stage users of Python who need to use Python in serious, enterprise level applications

Individuals who are familiar with data science and need to understand the optimal uses for Python



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