Practical Financial Data Analysis With Python Data Science


Conduct Financial Analysis With Forecasting & Machine Learning in Python. Obtain & Work With Real Financial Data

What you will learn

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

Description

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.


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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!

English
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Content

Introduction To the Course

Welcome To The Course
Data and Scripts Used in the Course
Introduction to the Python Data Science Environment
Upgraded Python3 Installation
Introduction to iPython/Jupyter

Read in and Preprocess Data From External Data Sources

Introduction to Pandas
Read in CSV Data
Read in Excel Data
Read in HTML Data
Basic Data Exploration With Pandas
Basic Data Handling With Conditional Statements
Drop Column/Row
Merging and Joining Data

Accessing Financial Data

Getting Stock Market Data From Yahoo
Convert Pandas Datareader to Pandas Dataframe Format
Historical Stock Data From Yahoo Finance
Welcome to Quandl
Accessing Quandl in Python
Accessing Financial Data Via ffn

Preprocessing Time Series Data in Python

Some Date Specific Python Functions
An Example of Time Series Data in Python
More Details on Datetime

Important Visualization Techniques For Financial Data

Principles of Data Visualization
Prep Up the Time Series Data
Line Charts For Examining Temporal Data
Plotting Multiple Lines on the Same Chart
Histograms-Visualize the Distribution of Continuous Numerical Variables
Visualise the Daily Returns
Visualize the Daily Percent Change
Visualize the Cumulative Returns
Correlation Between Stocks
Correlation Betwen Present and Future
Visualize the Relationship Between Multiple Stocks
Another Way of Correlation Visalization
Candlesticks Visualization

Basic Time Series For Deriving Patterns and Forecasts From Financial Data

Moving Averages/Rolling Means
More Moving Averages
Different Components of Time Series Data
Test For Stationarity: ADF Test Theory
Implement the ADF Test in Python
Make Your Time Series Stationary
Other Ways Of Making Time Series Data Stationary
Theory Behind Exponential Smoothing
Smooth Exponential Smoothing-Primer
How Good is SES For Forecasting?
Holt’s Linear Method For Forecasting
Theory Behind ARIMA
Implement Practical ARIMA For Time Series Forecasting

Machine Learning For Financial Data Forecasting

What Is Machine Learning?
Setting Up the Analysis in Facebook’s Prophet
Implement the Prophet Model
Use Prophet to Forecast to the Future
Prophet Results
Theory of k-NN (k-Nearest Neighbours)
kNN Regression Predictive Model
More KNN
Theory of Random Forests (RF)
Implement RF Regression For Forecasting
Ordinary Linear Squares (OLS) Regression-Theory
Implement OLS For Forecasting

Deep Learning Based Forecasting

Some Theoretical Concepts
What Is Keras?
Install Keras On Windows
Install Keras On Mac
Implement Keras Based LSTM On Stock Data
Tackling Unseen Values