Python & Machine Learning for Financial Analysis

BY
Udemy

Mode

Online

Fees

₹ 499 3499

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course and certificate fees

Fees information
₹ 499  ₹3,499
certificate availability

Yes

certificate providing authority

Udemy

The syllabus

Course Introduction, Success Tips and Key Learning Outcomes

  • Welcome Message
  • Introduction, Success Tips & Best Practices and Key Learning Outcomes
  • Course Outline and Key Learning Outcomes
  • Environment Setup & Course Materials Download
  • Google Colab Walkthrough
  • Python for Data Science Learning Path
  • Study Tips For Success

**********Part #1: Python Programming Fundamentals***********

  • Introduction to Part #1: Python Programming Fundamentals

Python 101: Variables Assignment, Math Operation, Precedence and Print/Get

  • Colab Notebooks - Variables Assignment, Math Ops, Precedence, and Print/Get
  • Variable assignment
  • Math operations
  • Precedence
  • Print operation
  • Get User Input

Python 101: Data Types

  • Colab Notebooks - Data Types
  • Booleans
  • List
  • Dictionaries
  • Strings
  • Tuples
  • Sets

Python 101: Comparison Operators, Logical Operators, and Conditional Statements

  • Colab Notebooks - Comparison Operators, Logical Operators and If Statements
  • Comparison operators
  • Logical operators
  • Conditional statements - Part #1
  • Conditional statements - Part #2

Python 101: Loops

  • Colab Notebooks - For/While Loops, Range, List Comprehension
  • For loops
  • Range
  • While Loops
  • Break a loop
  • Nested loops
  • List comprehension

Python 101: Functions

  • Colab Notebooks - Functions
  • Functions: built-in functions
  • Custom functions
  • Lambda expression
  • Map
  • Filter

Python 101: Files Operations

  • Colab Notebooks - Files Operations
  • Reading & Writing Text Files
  • Reading & Writing CSV Files

Python 101: Data Science Python Libraries for Data Analysis (Numpy)

  • Colab Notebooks - Numpy
  • Numpy basics
  • Built-in methods
  • Shape Length Type
  • Math operations
  • Slicing & indexing
  • Elements Selection

Python 101: Data Science Python Libraries for Data Analysis (Pandas)

  • Colab Notebooks - Pandas
  • Pandas: Introduction to Pandas and DataFrames
  • Reading HTML data, and applying functions, and sorting
  • DataFrame operations
  • Pandas with functions
  • Ordering and Sorting
  • Merging/joining/concatenation

Python 101: Data Visualization with Matplotlib

  • Colab Notebooks - Data Visualization with Matplotlib
  • Line Plot
  • Scatterplot
  • Pie Chart
  • Histograms
  • Multiple Plots
  • Subplots
  • 3D Plots
  • BoxPlot

Python 101: Data Visualization with Seaborn

  • Colab Notebooks - Data Visualization with Seaborn
  • Data Visualization with Seaborn - Part #1
  • Data Visualization with Seaborn - Part #2

********* Part #2: Python For Financial Analysis*********

  • Introduction to Part #2: Python for Financial Analysis

Stocks Data Analysis and Visualization in Python

  • Colab Notebooks - Stocks Data Analysis and Visualization in Python
  • Task 1
  • Task 2
  • Task 3
  • Task 4
  • Task 5
  • Task 6
  • Task 7
  • Task 8

Asset Allocation and Statistical Data Analysis

  • Colab Notebooks - Asset Allocation and Statistical Data Analysis
  • Task 1
  • Task 2
  • Task 3
  • Task 4
  • Task 5
  • Task 6
  • Task 7
  • Task 8

Capital Asset Pricing Model (CAPM)

  • Colab Notebooks - Capital Asset Pricing Model (CAPM)
  • Task 1
  • Task 2
  • Task 3
  • Task 4
  • Task 5
  • Task 6
  • Task 7

******* Part #3: Machine And Deep Learning In Finance *********

  • Introduction to Part #3: Machine and Deep Learning in Finance

Predict Stocks Future Prices Using Machine and Deep Learning

  • Colab Notebooks - Predict Future Stock Prices Using Machine/Deep Learning
  • Task 1
  • Task 2
  • Task 3
  • Task 4
  • Task 5
  • Task 6
  • Task 7
  • Task 8
  • Task 9
  • Task 10
  • Task 11
  • Task 12

Perform Bank Market Segmentation Using Unsupervised Machine Learning Techniques

  • Colab Notebooks - Perform Bank Customers Segmentation
  • Problem statement and business case
  • Import libraries and datasets
  • Visualize data
  • Understand K-means algorithm
  • Obtain optimal K
  • Apply K-means clustering
  • Principal component analysis
  • Intuition of autoencoders
  • Train autoencoder
  • Apply autoencoder

Perform Sentiment Analysis On Stocks Data Using Natural Language Processing

  • Colab Notebooks - Perform Sentiment Analysis on Stocks Data
  • Task 1
  • Task 2
  • Task 3
  • Task 4
  • Task 5
  • Task 6
  • Task 7
  • Task 8
  • Task 9
  • Task 10

Instructors

Dr Ryan Ahmed
Professor
Udemy

Other Masters, Ph.D, MBA

Mr Mitchell Bouchard

Mr Mitchell Bouchard
Filmmaker
Freelancer

Other Bachelors

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