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Importing Finance Data with Python from Free Web Sources

Name: Importing Finance Data with Python from Free Web Sources
Rating: 9.7 (283 reviews)

Get Historical Prices, Fundamentals, Metrics/Ratios etc. for thousands of Stocks, Bonds, Indexes, (Crypto-) Currencies

4.8

☆☆☆☆☆ 4.8/5

(283 reviews)

4,566 students

Created by

9.7

Classbaze Grade®

10.0

Freshness

9.0

Popularity

9.5

Material

Detailed Analysis »

Platform: Udemy

Price: check current price

Video: 7h 45m

Language: English

Next start: On Demand

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Classbaze Rating

Classbaze Grade®

9.7 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

10.0 / 10

This course was last updated on 6/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

9.0 / 10

We analyzed factors such as the rating (4.8/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

9.5 / 10

Video Score: 8.7 / 10

The course includes 7h 45m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.

The average video length is 7 hours 31 minutes of 1,582 Python courses on Udemy.

Detail Score: 9.8 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

6 articles.

3 resources.

0 exercise.

0 test.

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About this course

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What you need to START the course

Who can start this course?

General questions

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About the course

What can be the most critical and most expensive part when working with financial data?
Pandas coding? Creating some advanced Algorithms to analyse and optimize portfolios? Building solutions for Algorithmic Trading and Robo Advising? Maybe! But very often it is … getting the Data!
Financial Data is scarce and Premium Data Providers typically charge $20,000 p.a. and more!

However, in 95% of all cases where Finance Professionals or Researchers require Financial Data, it can actually be obtained from Free or low-priced web sources. Some of them provide powerful APIs and Python wrapper packages, which makes it easy and comfortable to import the data with and into Python.

+++ This course shows you how to get massive amounts of Financial Data from the web and provides downloadable Python coding templates (Jupyter Notebooks) for your convenience! +++

This course covers four different data sources and explains in detail how to install required Libraries and how to download and import the data with few lines of Python Code. You will have access to
•60+ Exchanges all around the world
•120,000+ Symbols/Instruments
•Historical Price and Volume Data for thousands of Stocks, Indexes, Mutual Funds and ETFs
•Foreign Exchange (FOREX): 150+ Physical Currencies / Currency Pairs
•500+ Digital- / Cryptocurrencies
•Fundamentals, Ratings, Historical Prices and Yields for Corporate Bonds
•Commodities (Crude Oil, Gold, Silver, etc.)
•Stock Options for 4,500 US Stocks
•Fundamentals, Metrics and Ratios for thousands of Stocks, Indexes, Mutual Funds and ETFs
•Balance Sheets
•Profit and Loss Statements (P&L)
•Cashflow Statements
•50+ Technical Indicators (e.g. SMA, Bollinger Bands)
•Real-time and Historical Data (back to 1960s)
•Streaming high-frequency real-time Data
•Stock Splits and Dividends and how these are reflected in Stock Prices
•Learn how Stock Prices are adjusted for Stock Splits and Dividends…
•… and use appropriately adjusted data for your tasks! (avoid the Pitfalls!)
•Build your own Financial Databases…
… And save thousands of USDs!

What are you waiting for? As always, I provide a 30-Days-Money-Back Guarantee. So, there is no risk for you!
Looking forward to seeing you in the course!

What can you learn from this course?

✓ Importing free / low-priced Financial Data from the Web with Python
✓ Installing the required Libraries and Packages
✓ Working with powerful APIs and Python wrapper packages
✓ Downloading Historical Prices and Fundamentals for thousands of Stocks, Indexes, Mutual Funds and ETF´s
✓ Downloading Historical Prices for Currencies (FOREX), Cryptocurrencies, Bonds & more
✓ Saving / Storing the Data locally
✓ Pandas Coding Crash Course

What you need to start the course?

• Some Python Basics
• A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
• An internet connection capable of streaming videos and downloading data
• Ideally first experience with Pandas Library (not necessary, a Pandas crash course is included in the course)

Who is this course is made for?

• Investment & Finance Professionals (and their Companies) spending thousands of USD p.a. on Financial Data.
• (Finance) Students and Researchers who need to work with large financial datasets with only small budgets.
• Everybody working occasionally with Financial Data.

Are there coupons or discounts for Importing Finance Data with Python from Free Web Sources ? What is the current price?

The course costs $18.99. And currently there is a 83% discount on the original price of the course, which was $109.99. So you save $91 if you enroll the course now.

The average price is $20.1 of 1,582 Python courses. So this course is 6% cheaper than the average Python course on Udemy.

Will I be refunded if I'm not satisfied with the Importing Finance Data with Python from Free Web Sources course?

YES, Importing Finance Data with Python from Free Web Sources has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Importing Finance Data with Python from Free Web Sources course, but there is a $91 discount from the original price ($109.99). So the current price is just $18.99.

Who will teach this course? Can I trust Alexander Hagmann?

Alexander Hagmann has created 14 courses that got 8,214 reviews which are generally positive. Alexander Hagmann has taught 71,877 students and received a 4.6 average review out of 8,214 reviews. Depending on the information available, we think that Alexander Hagmann is an instructor that you can trust.

Learn everything about

Alexander Hagmann

Data Scientist | Finance Professional | Entrepreneur

Alexander is a Data Scientist and Finance Professional with more than 10 years of experience in the Finance and Investment Industry.
He is also a Bestselling Udemy Instructor for
– Data Analysis/Manipulation with Pandas
– (Financial) Data Science
– Python for Business and Finance
– Algorithmic Trading
Alexander started his career in the traditional Finance sector and moved step-by-step into Data-driven and Artificial Intelligence-driven Finance roles. He is currently working on cutting-edge Fintech projects and creates solutions for Algorithmic Trading and Robo Investing. And Alexander is excited to share his knowledge with others here on Udemy. Students who completed his courses work in the largest and most popular tech and finance companies all over the world.
Alexander´s courses have one thing in common: Content and concepts are practical and real-world proven. The clear focus is on acquiring skills and understanding concepts rather than memorizing things.
Alexander holds a Master´s degree in Finance and passed all three CFA Exams (he is currently no active member of the CFA Institute).

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