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

Name: Mega Python - Pandas, Numpy, ML, APIs, GraphQL, AWS, PySpark
Rating: 4.7 (95 reviews)

One Mega course which covers programming, web development, APIs, DevOps, Financial World, Machine Learning and much more

Created byAdnan Waheed

Last updated 10/2023

English

What you'll 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..

Course content

52 sections • 387 lectures • 50h 40m total length

Install python4:28
Install python
Python3 and python0:25
The python interpreter4:40
The python interpreter
Writing our first python code3:50
Writing our first python code
Python IDLE program2:50
Python IDLE program
Installing Anaconda2:07
Installing Anaconda
Create your first python notebook8:27
Create your first python notebook
Jupyter Notebook - The Dashboard5:04
Jupyter Notebook - Coding commands11:44
Setting up IDE - Visual Studio Code4:23
Setting up IDE - Visual Studio Code

Variables and Strings14:50
Working with Comments1:55
How to load sample jupyter notebook1:48
Working with Strings and Numbers14:48
String functions10:19
String functions
String formatting7:06
Manipulating String16:37
Intro to Numbers13:58
Intro to Numbers
Fun with Numbers14:48
Numbers - modulus and floor division3:19
Built-in functions for numbers14:13
Built-in functions for numbers
More math functions with math module9:44
Formatting Numbers12:23
The double equality sign2:22
The double equality sign
Getting User Input3:47
Getting User Input
Python Operators11:05
Python Operators
Logical Operators4:27
Logical Operators
Comparison Operators2:39
Comparison Operators
Boolean Operators5:54
Boolean Operators

Python List9:33
Python List
Adding and removing elements in a list11:19
Adding and removing elements in a list
Popping items from a list8:16
Popping items from a list
Removing an item by value4:35
Removing an item by value
Sorting a list permanently or temporarily8:40
Permanent and temporarily sort
Reverse a list5:44
Reverse a list
Avoiding Index errors4:04
Avoiding Index errors
The list() constructor3:15
Looping an entire list7:05
Indentation6:12
Numerical List12:43
Numerical List
min, max and sum functions2:05
min, max and sum functions
Negative Indexing2:45
Negative Indexing
Multi-diementional list7:14
Multi-diementional list
Range function4:44
Range function
Looping multi-dimentional list10:44
Looping multi-dimentional list
Slicing of a list9:32
Slicing of a list
Slicing a List Part 211:08
Slicing a List Part 2
Iterate over multiple list5:26
Iterate over multiple list
Check if an item exist or not2:10
Check if an item exist or not
Count total occurrence of an item2:22
Count total occurrence of an item
Membership operators5:28
Membership operators
Find most common item4:44
Nested List8:34
Nested List
List Comprehensions16:25
List Comprehensions
List Comprehensions with if clause4:36
List Comprehensions with if clause
Nested List Comprehensions10:26
Nested List Comprehensions
Flatten a list of lists2:22
Flatten a list of lists
Remove duplicates from the list16:04
Remove duplicates from the list
Combine lists8:02

Introduction to Tuple7:47
tuple constructor3:27
tuple constructor
Access tuple items4:33
Access tuple items
Nested Tuples3:53
Nested Tuples
Slicing a tuple3:41
Slicing a tuple
Change Tuple item5:21
Change Tuple item
Writing over a tuple4:00
Change Tuple item?
Concatenation and Repetition2:36
Concatenation and Repetition
Iterate through a tuple1:28
Iterate through a tuple
Tuple Sorting5:05
Tuple Sorting
Tuple Packing & Unpacking8:11
Tuple Packing & Unpacking
Tuple count() method2:19
Tuple count() method
Tuple index() method6:16
Tuple index() method
all() function with Tuples4:26
all function with tuple
any() function with tuples4:05
any() function with tuples
sum() function with tuples2:28
sum() function with tuples
enumerate() function with tuples5:58
enumerate() function with tuples

Introduction to Numpy arrays8:06
array attributes - shape9:29
array attributes - ndim, size, dtype, nbytes4:25
Array Data types7:20
Create arrays from constant values14:01
Create arrays from space values9:36
Create arrays from set diagnals8:04
Create arrays from functions7:45
Indexing and slicing - Single dimension array6:27
Indexing and slicing - Multi-dimension array11:11
Creating views and copies5:10
Array Indexing4:11
Array indexing - multi dimensional array5:02
Boolean indexing4:57
Reshaping Numpy arrays5:51
Joining arrays9:56
Splitting arrays9:20
Searching arrays11:17
Sorting arrays4:55
Sorting techniques8:43
Sorting a matrix5:54
Iterating 1-D, 2D, and 3-D arrays6:51
Iterating arrays via nditer(), ndenumerate()7:23
Arithmetic operations6:43
Mathematical functions3:14
Comparing arrays4:04
Conditional functions5:59
Aggregation functions9:00

Check Equality2:43
Using asset_series for equality3:35
Calculate memory usage2:01
No of words in a column2:01
Convert one set of values to another8:18
Convert continuous data into categorical data4:12
Create a datetime column from multiple columns1:47
Resample by date time column4:53
Create a cross-tabluation4:54
Fill missing values using interpolation1:40
Transpose a wide DataFrame2:29
Create example DataFrames6:47
Identify missing rows4:20
Use query to avoid intermediate variables7:22
Reshape a DataFrame from wide to long format9:14

Requirements

No specific knowledge needed!

Description

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!

Who this course is for:

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

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

What you'll learn

Explore related topics

Course content

Getting Started10 lectures • 48min

*** COURSE - NEW UPDATES ***1 lecture • 1min

Python Strings and Numbers19 lectures • 2hr 46min

Python List30 lectures • 3hr 36min

Python Tuple17 lectures • 1hr 16min

Python Set4 lectures • 20min

*** NUMPY ****28 lectures • 3hr 25min

*** PANDAS ****6 lectures • 31min

Pandas Tricks15 lectures • 1hr 6min

**** BUILDING APIs ****13 lectures • 1hr 49min

Requirements

Description

Who this course is for: