Data Analysis with Python

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https://www.coursera.org/learn/data-analysis-with-python#syllabus

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A little background that I'm a self-learned technical artist creating VFX related tools with Python. Still not sure where to go with my life and just sort of browsing Python related job postings.

I came across these requirements that I assume you should know data analysis in order to perform such tasks? Something like this course? https://www.coursera.org/learn/data-analysis-with-python

• You will develop scalable systems that automatically collects large amount of marketing data, in a timely manner.
• You will architect and implement configurable data collection platform that is easily extendable, and can elegantly handle errors from external systems.
• You will work closely with the DevOps team to auto-scale the data acquisition system.
• You will work closely with the Product Manager team to find the right solutions for the system based on technical constraints and business requirements.
• You will help grow and lead a team of developers to achieve system requirements and business goals.

I'm looking for a very comprehensive Data Analytics MOOC that teaches everything from setting up a work environment (installing programs + readying workspace via folders) to producing an end product (either Capstone or something concrete). So, far, I haven't been able to find one. For example, I enrolled IBM's Data Analysis with Python course on Coursera. Even though it's a 'beginner' course, it leaves out important information and jumps right into syntax. So, does anyone know of a MOOC that provides exactly what I'm searching for?

Todo depende el camino que quieras tomar, si es data science (visualización y ML tradicional) toma cursos que enseñen conceptos y que no te encierren (IBM trata de usar su plataforma Watson para todo) tal vez este salve de ellos https://www.coursera.org/learn/data-analysis-with-python?specialization=ibm-data-analyst. Ahora el original de Andrew Ng utiliza octave / matlab pero enseña los conceptos mejor que cualquier otro curso que me he topado. Finalmente deeplearning. ai, es solo si te interesa el DL, está más actualizado pero muy enfocado a tensorflow, sin embargo es una buena introducción a los diferentes conceptos correspondientes.

TLDR; busca aprender conceptos y herramientas open source utilizadas en la industria.

Drop the python part, focus purely on statistics. That's how you get to statistical analysis. The python part is optional, you could use R or STATA or whatever you like.

There are plenty of resources online for data analysis with python: https://www.coursera.org/learn/data-analysis-with-python

but personally id rather focus on the statistical component more than which program to employ.

Your grooming yourself to be in healthcare IT then. That is a good field to be in.. Look at healthcare business analysts. You will want to know things like Python, PowerBi, Tableau, some data analytics.

IBM has a free course for python data analytics https://www.coursera.org/learn/data-analysis-with-python

I believe they also have a basic data analytics course. Your education should set you apart if you keep moving in your direction.

[Career] So I learned Python after getting my CFA...

Like many on this thread, Python was the biggest hype for me to pursue after getting my charter. As a result, I made it a personal goal of mine to learn Python in 2020. Here's what changed for me (career wise).

To start, with all the wfh and lockdown, I'm pretty pleased with myself that I managed to complete 3 courses since January:

1. Fundamental Comp Sci Python Course - https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/
2. Python Excel Manipulation which was offered my local CFA Society in Toronto - https://marqueegroup.ca/course/python-1-core-data-analysis/
3. Data Analysis with Python (teaches regression testing) - https://www.coursera.org/learn/data-analysis-with-python

Since then, I was able to automate over 10 hours of work weekly by streamlining reports (things you'd normally have to spent hours doing copying/pasting financial data can now be done in a click). My code grabs multiple data files on a weekly basis, cleans the data, merges them together, and then loads it in a database and locks into Tableau as a dashboard. It's pretty freaking awesome.

Here's the downside. After word got out of what I was able to do, everybodys now coming to me to build similar stuff for them (streamlining w/ python and loading into dashboards). I basically don't have anything else on my plate other than a backlog of these requests. My work allocation is severely one-sided.

In a recent catchup with my manager, he's even now lablled me as the "IT guy" on the team. And no disrepect to developers or anyone in IT, I did not study my CFA to become IT. So while everyone else on the team gets to work on things related to the business, I am told there is an opportunity for me to be promoted next year to "lead IT work" As a result, I'm drifting further away from actual investment-related work, but more technology focused work.

So to all the people wanting to learn Python/Tableau and Data Science etc... Maybe it's better to spend the time refining investment-related knowledge and soft skills rather than learning to code and risk being labelled as "IT". I know this could very well be a one-off experience, but just wanted to share what had happened to me. I know tech is very lucrative still, but I'm not sure I'd ever be as good as actual software developers or analytics professionals.

Happy to hear other people's experiences with Python and how being technical has/has not enabled them to progress in their careers.

https://github.com/andkret/Cookbook

SQL, visualización, un poco de estadística, y ya que estás usando Python: https://www.coursera.org/learn/data-analysis-with-python

No gonna lie mate its a long journey to get to the stage where you pick up a jupyter notebook over an excel spread sheet. You need a basic understanding of python to start which can be found anywhere for free on youtube. Then look into data analysis with Pandas, numpy and some of the graphing library like matplotlib / plotly. Plenty of course online about these core libraries in python -

https://www.datacamp.com/courses/pandas-foundations

https://www.kaggle.com/learn/pandas

https://www.coursera.org/learn/data-analysis-with-python

https://www.coursera.org/learn/python-for-data-visualization

So after a good understanding of python and its libraries you can start making jupyter notebooks. These are something like a extremely customisable but bare-bones word document that has python programming all through it.

They take longer to do analysis than excel, painful to make graphs and all round time sink. But my god if you take the time setting them up they output some of the most beautiful documents. The impact of handing a client something that looks like a research paper with formatted equations and code throughout over an excel spreadsheet is unbelievable. Its has become a defining thing my team does now for deliverables and makes us look top shit.

As you slowly get better with them you build up a personal library of reusable modelling notebooks just like you would in excel. You get to a stage where you have all these customised notebooks where you switch the new data in add the new company logos and hit run.

Here are a couple examples of notebooks: https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks#statistics-machine-learning-and-data-science