Mega Python Pandas, Numpy, ML, APIs, GraphQL, AWS, PySpark

Mega Python – Pandas, Numpy, ML, APIs, GraphQL, AWS, PySpark, available at $69.99, has an average rating of 4.1, with 410 lectures, based on 42 reviews, and has 691 subscribers.

You will learn about One Mega course 50+ hours with 30+ practical topics Pandas, Numpy, Machine Learning, AWS Services, GraphQL, APIs Developments Create and analyze projects via Python Pandas, Numpy libraries and more Learn about building APIs, working with Databases like MongoDB, Cassandra How to use Amazon S3, SQS and other services as a DevOps Work with PySpark and DataFrames Analyze practical projects like Global Earthquakes, Monkey Pox Virus and more.. This course is ideal for individuals who are Anyone who want to explore the world of Python or Anyone who want to transition from Excel into Python or Anyone who want to learn how to do time series analysis on any global financial market instruments. i.e. Stocks, Indexes, Crypto and more or Anyone who wants to have a single mega-course on Python which covers various practical topics It is particularly useful for Anyone who want to explore the world of Python or Anyone who want to transition from Excel into Python or Anyone who want to learn how to do time series analysis on any global financial market instruments. i.e. Stocks, Indexes, Crypto and more or Anyone who wants to have a single mega-course on Python which covers various practical topics.

Enroll now: Mega Python – Pandas, Numpy, ML, APIs, GraphQL, AWS, PySpark

Summary

Title: Mega Python – Pandas, Numpy, ML, APIs, GraphQL, AWS, PySpark

Price: $69.99

Average Rating: 4.1

Number of Lectures: 410

Number of Published Lectures: 387

Number of Curriculum Items: 410

Number of Published Curriculum Objects: 387

Original Price: $74.99

Quality Status: approved

Status: Live

What You Will Learn

One Mega course 50+ hours with 30+ practical topics

Pandas, Numpy, Machine Learning, AWS Services, GraphQL, APIs Developments

Create and analyze projects via Python Pandas, Numpy libraries and more

Learn about building APIs, working with Databases like MongoDB, Cassandra

How to use Amazon S3, SQS and other services as a DevOps

Work with PySpark and DataFrames

Analyze practical projects like Global Earthquakes, Monkey Pox Virus and more..

Who Should Attend

Anyone who want to explore the world of Python

Anyone who want to transition from Excel into Python

Anyone who want to learn how to do time series analysis on any global financial market instruments. i.e. Stocks, Indexes, Crypto and more

Anyone who wants to have a single mega-course on Python which covers various practical topics

Target Audiences

Anyone who want to explore the world of Python

Anyone who want to transition from Excel into Python

Anyone who want to learn how to do time series analysis on any global financial market instruments. i.e. Stocks, Indexes, Crypto and more

Anyone who wants to have a single mega-course on Python which covers various practical topics

Welcome to Mega Python!

This course will guide you through everything you need to know to use Python for practical use and more! I’ve worked for Bloomberg for 17+ years and will present the knowledge to help you in this course.

This course is a ‘Mega Course’, packed with so many practical topics to help you success practically! We’ll cover the following topics:

Python Fundamentals

NumPy for High Speed Numerical Processing

Pandas for Efficient Data Analysis

Matplotlib for Data Visualization

Pandas Time Series Analysis Techniques

Statsmodels

Importing financial markets data

Create interactive financial charts with plotly

Time series analysis with indexing, filling and resampling

Create interactive data apps with streamlit

Data visualization with Dash

Why you should listen to me

In my career, I have built an extensive level of expertise and experience in both areas: Finance and Coding

Finance:

17 years experience in Bloomberg for the Finance and Investment Industry

Build various financial markets analytics companies like

KlickAnalytics,

Cryptoquote

ClickAPIs and more

Python & Pandas:

My existing companies extensively used python based models and algorithms

Code, models, and workflows are Real World Project-proven

Best Seller author on Udemy

e.g. PostgreSQL Bootcamp: Go from Beginner to Advanced, 60+ Hours course

Master Redis – From Beginner to Advanced, 20+ hours

Python for Finance

What are you waiting for? Guaranteed Satisfaction: Otherwise, get your money back with 30-day money back guaranteed by Udemy.

Looking Forward to seeing you in the Course!

LETS GET STARTED!

Course Curriculum

Chapter 1: Getting Started

Lecture 1: Install python

Lecture 2: Python3 and python

Lecture 3: The python interpreter

Lecture 4: Writing our first python code

Lecture 5: Python IDLE program

Lecture 6: Installing Anaconda

Lecture 7: Create your first python notebook

Lecture 8: Jupyter Notebook – The Dashboard

Lecture 9: Jupyter Notebook – Coding commands

Lecture 10: Setting up IDE – Visual Studio Code

Chapter 2: *** COURSE – NEW UPDATES ***

Lecture 1: New Updates

Chapter 3: Python Strings and Numbers

Lecture 1: Variables and Strings

Lecture 2: Working with Comments

Lecture 3: How to load sample jupyter notebook

Lecture 4: Working with Strings and Numbers

Lecture 5: String functions

Lecture 6: String formatting

Lecture 7: Manipulating String

Lecture 8: Intro to Numbers

Lecture 9: Fun with Numbers

Lecture 10: Numbers – modulus and floor division

Lecture 11: Built-in functions for numbers

Lecture 12: More math functions with math module

Lecture 13: Formatting Numbers

Lecture 14: The double equality sign

Lecture 15: Getting User Input

Lecture 16: Python Operators

Lecture 17: Logical Operators

Lecture 18: Comparison Operators

Lecture 19: Boolean Operators

Chapter 4: Python List

Lecture 1: Python List

Lecture 2: Adding and removing elements in a list

Lecture 3: Popping items from a list

Lecture 4: Removing an item by value

Lecture 5: Sorting a list permanently or temporarily

Lecture 6: Reverse a list

Lecture 7: Avoiding Index errors

Lecture 8: The list() constructor

Lecture 9: Looping an entire list

Lecture 10: Indentation

Lecture 11: Numerical List

Lecture 12: min, max and sum functions

Lecture 13: Negative Indexing

Lecture 14: Multi-diementional list

Lecture 15: Range function

Lecture 16: Looping multi-dimentional list

Lecture 17: Slicing of a list

Lecture 18: Slicing a List Part 2

Lecture 19: Iterate over multiple list

Lecture 20: Check if an item exist or not

Lecture 21: Count total occurrence of an item

Lecture 22: Membership operators

Lecture 23: Find most common item

Lecture 24: Nested List

Lecture 25: List Comprehensions

Lecture 26: List Comprehensions with if clause

Lecture 27: Nested List Comprehensions

Lecture 28: Flatten a list of lists

Lecture 29: Remove duplicates from the list

Lecture 30: Combine lists

Chapter 5: Python Tuple

Lecture 1: Introduction to Tuple

Lecture 2: tuple constructor

Lecture 3: Access tuple items

Lecture 4: Nested Tuples

Lecture 5: Slicing a tuple

Lecture 6: Change Tuple item

Lecture 7: Writing over a tuple

Lecture 8: Concatenation and Repetition

Lecture 9: Iterate through a tuple

Lecture 10: Tuple Sorting

Lecture 11: Tuple Packing & Unpacking

Lecture 12: Tuple count() method

Lecture 13: Tuple index() method

Lecture 14: all() function with Tuples

Lecture 15: any() function with tuples

Lecture 16: sum() function with tuples

Lecture 17: enumerate() function with tuples

Chapter 6: Python Set

Lecture 1: Create, Set Constructor, Add and remove methods

Lecture 2: Find Length, clear all elements, and iterate all elements

Lecture 3: Check if an item exist or not

Lecture 4: pop method

Chapter 7: *** NUMPY ****

Lecture 1: Introduction to Numpy arrays

Lecture 2: array attributes – shape

Lecture 3: array attributes – ndim, size, dtype, nbytes

Lecture 4: Array Data types

Lecture 5: Create arrays from constant values

Lecture 6: Create arrays from space values

Lecture 7: Create arrays from set diagnals

Lecture 8: Create arrays from functions

Lecture 9: Indexing and slicing – Single dimension array

Lecture 10: Indexing and slicing – Multi-dimension array

Lecture 11: Creating views and copies

Lecture 12: Array Indexing

Instructors

Adnan Waheed
Founder KlickAnalytics and ex-Bloomberg employee

Rating Distribution

1 stars: 3 votes

2 stars: 0 votes

3 stars: 3 votes

4 stars: 7 votes

5 stars: 29 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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