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Practical Financial Data Analysis With Python Data Science

Conduct Financial Analysis With Forecasting & Machine Learning in Python. Obtain & Work With Real Financial Data
4.5
4.5/5
(51 reviews)
502 students
Created by

8.8

Classbaze Grade®

7.8

Freshness

8.6

Popularity

9.3

Material

Conduct Financial Analysis With Forecasting & Machine Learning in Python. Obtain & Work With Real Financial Data
Platform: Udemy
Video: 5h 58m
Language: English
Next start: On Demand

Best Financial Analysis classes:

Classbaze Rating

Classbaze Grade®

8.8 / 10

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

Freshness

7.8 / 10
This course was last updated on 7/2020.

Course content can become outdated quite quickly.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

8.6 / 10
We analyzed factors such as the rating (4.5/5) 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

9.3 / 10
Video Score: 8.5 / 10
The course includes 5h 58m 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 4 hours 25 minutes of 111 Financial Analysis courses on Udemy.
Detail Score: 10.0 / 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: 9.5 / 10

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

This course contains:

0 article.
1 resources.
0 exercise.
0 test.

In this page

About the course

THIS IS YOUR COMPLETE GUIDE TO FINANCIAL DATA ANALYSIS IN PYTHON!
This course is your complete guide to analyzing real-world financial data using Python. All the main aspects of analyzing financial data- statistics, data visualization, time series analysis and machine learning will be covered in depth.
If you take this course, you can do away with taking other courses or buying books on Python-based data analysis.  
In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By becoming proficient in analysing financial data in Python, you can give your company a competitive edge and boost your career to the next level.
                                                       
LEARN FROM AN EXPERT DATA SCIENTIST  WITH +5 YEARS OF EXPERIENCE:
Hey, my name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment), graduate. I recently finished a PhD at Cambridge University.
I have +5 years of experience in analyzing real-life data from different sources using data science-related techniques and I have produced many publications for international peer-reviewed journals.
 Over the course of my research, I realised almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic.
So, unlike other instructors, I dig deep into the data science features of R and gives you a one-of-a-kind grounding in data science-related topics!
You will go all the way from carrying out data reading & cleaning to finally implementing powerful statistical and machine learning algorithms for analyzing financial data.
Among other things:
•You will be introduced to powerful Python-based packages for financial data analysis.
•You will be introduced to both the commonly used techniques, visualization methods and machine/deep learning techniques that can be implemented for financial data.
•& you will learn to apply these frameworks to real-life data including temporal stocks and financial data.  
NO PRIOR PYTHON OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED!
You’ll start by absorbing the most valuable Python Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python.
My course will help you implement the methods using REAL DATA obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real-life.
After taking this course, you’ll easily use the common time-series and financial analysis packages in Python…
You’ll even understand the underlying concepts to understand what algorithms and methods are best suited for your data.
We will work with real data and you will have access to all the code and data used in the course. 
JOIN MY COURSE NOW!

What can you learn from this course?

✓ LEARN To Obtain Real World Financial Data FREE From Yahoo and Quandl
✓ BE ABLE To Read In, Pre-process & Visualize Time Series Data
✓ IMPLEMENT Common Data Processing And Visualisation Techniques For Financial Data in Python
✓ LEARN How To Use Different Python-based Packages For Financial Analysis
✓ MODEL Time Series Data To Forecast Future Values With Classical Time Series Techniques
✓ USE Machine Learning Regression For Building Predictive Models of Stock prices
✓ LEARN How to Use Facebook’s Powerful Prophet Algorithm For Modelling Financial Data
✓ IMPLEMENT Deep learning methods such as LSTM For Forecasting Stock Data

What you need to start the course?

• Prior Familiarity With The Interface Of Jupiter Notebooks and Package Installation
• Prior Exposure to Basic Statistical Techniques (Such As p-Values, Mean, Variance)
• Be Able To Carry Out Data Reading And Pre-Processing Tasks Such As Data Cleaning In Python
• Interest In Working With Time Series Data Or Data With A Time Component To Them

Who is this course is made for?

• Anyone Who Wants Master Financial Data Analysis In Python
• Anyone Who Wants To Become Proficient In Financial Data Analysis Working With Real Life Data
• People Interested in Applying Machine Learning Techniques to Financial Data
• Anyone Who Wants To Become An Expert Data Scientist

Are there coupons or discounts for Practical Financial Data Analysis With Python Data Science ? What is the current price?

The course costs $17.99. And currently there is a 82% discount on the original price of the course, which was $99.99. So you save $82 if you enroll the course now.
The average price is $19.2 of 111 Financial Analysis courses. So this course is 6% cheaper than the average Financial Analysis course on Udemy.

Will I be refunded if I'm not satisfied with the Practical Financial Data Analysis With Python Data Science course?

YES, Practical Financial Data Analysis With Python Data Science 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 Practical Financial Data Analysis With Python Data Science course, but there is a $82 discount from the original price ($99.99). So the current price is just $17.99.

Who will teach this course? Can I trust Minerva Singh?

Minerva Singh has created 46 courses that got 16,390 reviews which are generally positive. Minerva Singh has taught 82,987 students and received a 4.5 average review out of 16,390 reviews. Depending on the information available, we think that Minerva Singh is an instructor that you can trust.
Bestselling Instructor & Data Scientist(Cambridge Uni)
I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year’s experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics. I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly regarded academic journals such as Remote Sensing and given guest lectures on prestigious forums such as Open Data Science Conference (ODSC).
Browse all courses by on Classbaze.

8.8

Classbaze Grade®

7.8

Freshness

8.6

Popularity

9.3

Material

Platform: Udemy
Video: 5h 58m
Language: English
Next start: On Demand

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