SlideShare a Scribd company logo
Python in Industry
Dharmit Shah
GOAL
To make you aware of awesome career options for
Python Programmers!
Topics
● Who uses Python? How do they use Python?
● What kind of problems does Python help solve?
● What are different career options for a Python programmer?
● How to become a better Python programmer?
Who am I?
● Developer at Red Hat
● Working on open source projects that are built using Python & Golang
● I organize and speak at various Meetups in Ahmedabad
○ Docker
○ Ansible
○ Kubernetes
○ DigitalOcean
● Firm believer in lifelong learning
Brief intro to Python
History of Python
● Developed by Guido van Rossum in late 1980s
● Named after a TV show called “Monty Python”
● Python interpreter developed using C language
● Open source - so you can contribute to it as well!
Which organizations use Python?
● Red Hat
● YouTube
● Instagram, Facebook
● NASA
● Google
● Microsoft
● ...many more
How do organizations use Python?
● Web framework for backend
● Data analysis (scientific and numeric computing)
● Machine learning & Artificial Intelligence
● Automating the boring tasks
● Configuration management
● Web Scraping
● Embedded systems
Web Frameworks
What is a framework and why use it?
● Framework is a collection of code that makes it easier to develop applications
● Web framework makes it easy to write, scale and maintain web applications
● They provide features like:
○ URL routing
○ Database manipulation
○ Security
○ Session control
● Different frameworks have different set of features
django (https://www.djangoproject.com/)
● Most popular web framework of Python
● Provides a lot of features to develop websites; probably most feature-rich!
● Works with number of databases using ORM (no need to learn SQL!)
● But doesn’t work so well with NoSQL
● Has a huge community of developers using it
● Extensive documentation available online!
Flask (http://flask.pocoo.org)
● A minimalistic framework
● Very easy to get started with as a beginner
● Doesn’t follow batteries included approach of django
● Excellent online documentation and great community of developers
Few other frameworks
● Bottle (http://bottlepy.org/docs/dev/index.html)
● Pyramid (http://www.pylonsproject.org/projects/pyramid/about)
● Falcon (https://falconframework.org/)
Data Analysis
What is Data Analysis?
● Process of producing meaningful information from a big (huge?) chunk of data
● Encompasses various other domains:
○ Data Mining
○ Business Intelligence
○ Predictive Analysis, etc.
● Closely related to Data Visualization
● Helps make decisions that might change the future!
SciPy Ecosystem (https://www.scipy.org/index.html)
● An ecosystem of opensource software for maths, science & engineering
● NumPy
○ Package for numerical computation.
○ Helps define numerical arrays and matrices
○ Perform operations on arrays & matrices
● SciPy library
○ Collection of numerical algorithms and domain-specific toolboxes
○ Signal processing, optimization, statistics and more
SciPy Ecosystem (contd..)
● Matplotlib
○ Popular plotting package
○ Helps plot 2D and basic 3D plots
● Pandas: provides high-performance, easy to use data structures
● scikit-image: collection of algorithms for image processing
● scikit-learn: collection of algorithms for machine learning
● IPython: an alternate interface to interact with Python interpreter
Data Analysis
● Data is continuously increasing!
● Making sense of data is a hot skill
● People from varying educational background are picking it up!
● Jobs & opportunities up for grabs!
● Plenty of MOOC (massive open online course) available
Machine Learning
And
Artificial Intelligence
What is ML and AI?
● Ability of computers to learn without being programmed!
● Ability to perform data driven decisions
● Significant overlap with Data Mining
● ML focuses on prediction, based on known properties
● Data Mining focuses on the discovery of (previously) unknown properties
Frameworks and libraries
● Mostly the same as the ones we covered in Data Analysis
● It’s about how we use those libraries
● Also, TensorFlow
Automating the
Boring Tasks
A book!
● Automating tasks that would otherwise take hours if done manually
● Great book titled “Automate the Boring Stuff with Python”
○ Search for text in a file or across multiple files
○ Create, update, move, and rename files and folders
○ Search the Web and download online content
○ Update and format data in Excel spreadsheets of any size
○ Split, merge, watermark, and encrypt PDFs
○ Send reminder emails and text notifications
○ Fill out online forms
● https://automatetheboringstuff.com/ (free to read online!)
Python for
Electronics
Engineers
Python and Embedded systems
● Steadily increasing adaption
● Boards
○ MicroPython
○ Raspberry Pi
○ Arduino
● Lots and lots of documentation and tutorials available online!
Few projects
● Motion sensor with alarm
● Home automation system
● Use Lego toys to make robotic cars
● Send board to space (PITS : Pi In The Sky)
● ...many, many more!
Web Scraping
What is it?
● Process of extracting data from websites
● Data from websites is downloaded for later analysis
● This data is then extracted
● The extracted content may be parsed, searched, reformatted, etc.
Python tools for scraping
● BeautifulSoup
● Mechanize
● Scrapemark
● Scrapy
What else can be done with Python?
● Chatbots
● Blockchain
● Configuration Management tools
● Desktop and mobile applications
Career Options
● Developer
○ Backend developer
○ Full Stack developer
● System Administrator
● Data Scientist
● Many more specialized roles!
How to
get better at
Python?
Talk is cheap, write some code!
● Participate in open source projects
● Read more Python code and then write more
● Subscribe to newsletters
○ Python Weekly
○ Import Python
○ Pycoder’s Weekly
○ Full Stack Python
● Read and learn from ton of free online material about Python
● Find a mentor if you can
https://goo.gl/yf7VEL
Feedback!
Contact Me: https://dharmitshah.com

More Related Content

What's hot

Python programming
Python programmingPython programming
Python programming
Megha V
 
Data Analysis in Python-NumPy
Data Analysis in Python-NumPyData Analysis in Python-NumPy
Data Analysis in Python-NumPy
Devashish Kumar
 
Data structure and algorithm
Data structure and algorithmData structure and algorithm
Data structure and algorithm
Trupti Agrawal
 
Python Book/Notes For Python Book/Notes For S.Y.B.Sc. I.T.
Python Book/Notes For Python Book/Notes For S.Y.B.Sc. I.T.Python Book/Notes For Python Book/Notes For S.Y.B.Sc. I.T.
Python Book/Notes For Python Book/Notes For S.Y.B.Sc. I.T.
Niraj Bharambe
 
Applications of data structures
Applications of data structuresApplications of data structures
Applications of data structures
Wipro
 
Data structures and algorithms
Data structures and algorithmsData structures and algorithms
Data structures and algorithms
Julie Iskander
 
Building Named Entity Recognition Models Efficiently using NERDS
Building Named Entity Recognition Models Efficiently using NERDSBuilding Named Entity Recognition Models Efficiently using NERDS
Building Named Entity Recognition Models Efficiently using NERDS
Sujit Pal
 
Looping statement in python
Looping statement in pythonLooping statement in python
Looping statement in python
RaginiJain21
 
Introduction to Python
Introduction to Python  Introduction to Python
Introduction to Python
Mohammed Sikander
 
Computability - Tractable, Intractable and Non-computable Function
Computability - Tractable, Intractable and Non-computable FunctionComputability - Tractable, Intractable and Non-computable Function
Computability - Tractable, Intractable and Non-computable Function
Reggie Niccolo Santos
 
Python for Data Science
Python for Data SciencePython for Data Science
Python for Data Science
Harri Hämäläinen
 
What is Multithreading In Python | Python Multithreading Tutorial | Edureka
What is Multithreading In Python | Python Multithreading Tutorial | EdurekaWhat is Multithreading In Python | Python Multithreading Tutorial | Edureka
What is Multithreading In Python | Python Multithreading Tutorial | Edureka
Edureka!
 
C presentation
C presentationC presentation
Introduction to python programming
Introduction to python programmingIntroduction to python programming
Introduction to python programming
Srinivas Narasegouda
 
Programming with Python
Programming with PythonProgramming with Python
Programming with Python
Rasan Samarasinghe
 
Python - Numpy/Pandas/Matplot Machine Learning Libraries
Python - Numpy/Pandas/Matplot Machine Learning LibrariesPython - Numpy/Pandas/Matplot Machine Learning Libraries
Python - Numpy/Pandas/Matplot Machine Learning Libraries
Andrew Ferlitsch
 
Presentation on python
Presentation on pythonPresentation on python
Presentation on python
Venkat Projects
 
Time and space complexity
Time and space complexityTime and space complexity
Time and space complexity
Ankit Katiyar
 
Zero to Hero - Introduction to Python3
Zero to Hero - Introduction to Python3Zero to Hero - Introduction to Python3
Zero to Hero - Introduction to Python3
Chariza Pladin
 
Intro to Python
Intro to PythonIntro to Python
Intro to Python
primeteacher32
 

What's hot (20)

Python programming
Python programmingPython programming
Python programming
 
Data Analysis in Python-NumPy
Data Analysis in Python-NumPyData Analysis in Python-NumPy
Data Analysis in Python-NumPy
 
Data structure and algorithm
Data structure and algorithmData structure and algorithm
Data structure and algorithm
 
Python Book/Notes For Python Book/Notes For S.Y.B.Sc. I.T.
Python Book/Notes For Python Book/Notes For S.Y.B.Sc. I.T.Python Book/Notes For Python Book/Notes For S.Y.B.Sc. I.T.
Python Book/Notes For Python Book/Notes For S.Y.B.Sc. I.T.
 
Applications of data structures
Applications of data structuresApplications of data structures
Applications of data structures
 
Data structures and algorithms
Data structures and algorithmsData structures and algorithms
Data structures and algorithms
 
Building Named Entity Recognition Models Efficiently using NERDS
Building Named Entity Recognition Models Efficiently using NERDSBuilding Named Entity Recognition Models Efficiently using NERDS
Building Named Entity Recognition Models Efficiently using NERDS
 
Looping statement in python
Looping statement in pythonLooping statement in python
Looping statement in python
 
Introduction to Python
Introduction to Python  Introduction to Python
Introduction to Python
 
Computability - Tractable, Intractable and Non-computable Function
Computability - Tractable, Intractable and Non-computable FunctionComputability - Tractable, Intractable and Non-computable Function
Computability - Tractable, Intractable and Non-computable Function
 
Python for Data Science
Python for Data SciencePython for Data Science
Python for Data Science
 
What is Multithreading In Python | Python Multithreading Tutorial | Edureka
What is Multithreading In Python | Python Multithreading Tutorial | EdurekaWhat is Multithreading In Python | Python Multithreading Tutorial | Edureka
What is Multithreading In Python | Python Multithreading Tutorial | Edureka
 
C presentation
C presentationC presentation
C presentation
 
Introduction to python programming
Introduction to python programmingIntroduction to python programming
Introduction to python programming
 
Programming with Python
Programming with PythonProgramming with Python
Programming with Python
 
Python - Numpy/Pandas/Matplot Machine Learning Libraries
Python - Numpy/Pandas/Matplot Machine Learning LibrariesPython - Numpy/Pandas/Matplot Machine Learning Libraries
Python - Numpy/Pandas/Matplot Machine Learning Libraries
 
Presentation on python
Presentation on pythonPresentation on python
Presentation on python
 
Time and space complexity
Time and space complexityTime and space complexity
Time and space complexity
 
Zero to Hero - Introduction to Python3
Zero to Hero - Introduction to Python3Zero to Hero - Introduction to Python3
Zero to Hero - Introduction to Python3
 
Intro to Python
Intro to PythonIntro to Python
Intro to Python
 

Similar to Python in Industry

Django on app engine
Django on app engineDjango on app engine
Django on app engine
benpotato
 
An overview of data and web-application development with Python
An overview of data and web-application development with PythonAn overview of data and web-application development with Python
An overview of data and web-application development with Python
Sivaranjan Goswami
 
Dynatech presentation for TSI Career Day
Dynatech presentation for TSI Career DayDynatech presentation for TSI Career Day
Dynatech presentation for TSI Career Day
Artur Babyuk
 
Programming for non tech entrepreneurs
Programming for non tech entrepreneursProgramming for non tech entrepreneurs
Programming for non tech entrepreneurs
Rodrigo Gil
 
Pentester++
Pentester++Pentester++
Pentester++
CTruncer
 
The Professional Programmer
The Professional ProgrammerThe Professional Programmer
The Professional Programmer
Dave Cross
 
divyanshBajaj.pptx
divyanshBajaj.pptxdivyanshBajaj.pptx
divyanshBajaj.pptx
lakshyarajSinghchund1
 
Python for All
Python for All Python for All
Python for All
Pragya Goyal
 
Python For All | Software Professionals, QA & DevOps professionals
Python For All | Software Professionals, QA & DevOps professionalsPython For All | Software Professionals, QA & DevOps professionals
Python For All | Software Professionals, QA & DevOps professionals
Nilesh Sutar
 
Monitoring Big Data Systems - "The Simple Way"
Monitoring Big Data Systems - "The Simple Way"Monitoring Big Data Systems - "The Simple Way"
Monitoring Big Data Systems - "The Simple Way"
Demi Ben-Ari
 
Life in CSE.pptx
Life in CSE.pptxLife in CSE.pptx
Life in CSE.pptx
VedVekhande
 
What drives Innovation? Innovations And Technological Solutions for the Distr...
What drives Innovation? Innovations And Technological Solutions for the Distr...What drives Innovation? Innovations And Technological Solutions for the Distr...
What drives Innovation? Innovations And Technological Solutions for the Distr...
Stefano Fago
 
Data analysis with Pandas and Spark
Data analysis with Pandas and SparkData analysis with Pandas and Spark
Data analysis with Pandas and Spark
Felix Crisan
 
Python_basics_tuples_sets_lists_control_loops.ppt
Python_basics_tuples_sets_lists_control_loops.pptPython_basics_tuples_sets_lists_control_loops.ppt
Python_basics_tuples_sets_lists_control_loops.ppt
VGaneshKarthikeyan
 
Why learn python in 2017?
Why learn python in 2017?Why learn python in 2017?
Why learn python in 2017?
Karolis Ramanauskas
 
Apresentação - Minicurso de Introdução a Python, Data Science e Machine Learning
Apresentação - Minicurso de Introdução a Python, Data Science e Machine LearningApresentação - Minicurso de Introdução a Python, Data Science e Machine Learning
Apresentação - Minicurso de Introdução a Python, Data Science e Machine Learning
Arthur Emanuel
 
Python. Why to learn?
Python. Why to learn?Python. Why to learn?
Python. Why to learn?
Oleh Korkh
 
Workflow Engines + Luigi
Workflow Engines + LuigiWorkflow Engines + Luigi
Workflow Engines + Luigi
Vladislav Supalov
 
Interconnection Automation For All - Extended - MPS 2023
Interconnection Automation For All - Extended - MPS 2023Interconnection Automation For All - Extended - MPS 2023
Interconnection Automation For All - Extended - MPS 2023
Chris Grundemann
 
Practical automation for beginners
Practical automation for beginnersPractical automation for beginners
Practical automation for beginners
Seoweon Yoo
 

Similar to Python in Industry (20)

Django on app engine
Django on app engineDjango on app engine
Django on app engine
 
An overview of data and web-application development with Python
An overview of data and web-application development with PythonAn overview of data and web-application development with Python
An overview of data and web-application development with Python
 
Dynatech presentation for TSI Career Day
Dynatech presentation for TSI Career DayDynatech presentation for TSI Career Day
Dynatech presentation for TSI Career Day
 
Programming for non tech entrepreneurs
Programming for non tech entrepreneursProgramming for non tech entrepreneurs
Programming for non tech entrepreneurs
 
Pentester++
Pentester++Pentester++
Pentester++
 
The Professional Programmer
The Professional ProgrammerThe Professional Programmer
The Professional Programmer
 
divyanshBajaj.pptx
divyanshBajaj.pptxdivyanshBajaj.pptx
divyanshBajaj.pptx
 
Python for All
Python for All Python for All
Python for All
 
Python For All | Software Professionals, QA & DevOps professionals
Python For All | Software Professionals, QA & DevOps professionalsPython For All | Software Professionals, QA & DevOps professionals
Python For All | Software Professionals, QA & DevOps professionals
 
Monitoring Big Data Systems - "The Simple Way"
Monitoring Big Data Systems - "The Simple Way"Monitoring Big Data Systems - "The Simple Way"
Monitoring Big Data Systems - "The Simple Way"
 
Life in CSE.pptx
Life in CSE.pptxLife in CSE.pptx
Life in CSE.pptx
 
What drives Innovation? Innovations And Technological Solutions for the Distr...
What drives Innovation? Innovations And Technological Solutions for the Distr...What drives Innovation? Innovations And Technological Solutions for the Distr...
What drives Innovation? Innovations And Technological Solutions for the Distr...
 
Data analysis with Pandas and Spark
Data analysis with Pandas and SparkData analysis with Pandas and Spark
Data analysis with Pandas and Spark
 
Python_basics_tuples_sets_lists_control_loops.ppt
Python_basics_tuples_sets_lists_control_loops.pptPython_basics_tuples_sets_lists_control_loops.ppt
Python_basics_tuples_sets_lists_control_loops.ppt
 
Why learn python in 2017?
Why learn python in 2017?Why learn python in 2017?
Why learn python in 2017?
 
Apresentação - Minicurso de Introdução a Python, Data Science e Machine Learning
Apresentação - Minicurso de Introdução a Python, Data Science e Machine LearningApresentação - Minicurso de Introdução a Python, Data Science e Machine Learning
Apresentação - Minicurso de Introdução a Python, Data Science e Machine Learning
 
Python. Why to learn?
Python. Why to learn?Python. Why to learn?
Python. Why to learn?
 
Workflow Engines + Luigi
Workflow Engines + LuigiWorkflow Engines + Luigi
Workflow Engines + Luigi
 
Interconnection Automation For All - Extended - MPS 2023
Interconnection Automation For All - Extended - MPS 2023Interconnection Automation For All - Extended - MPS 2023
Interconnection Automation For All - Extended - MPS 2023
 
Practical automation for beginners
Practical automation for beginnersPractical automation for beginners
Practical automation for beginners
 

More from Dharmit Shah

Introducing CentOS container pipeline
Introducing CentOS container pipelineIntroducing CentOS container pipeline
Introducing CentOS container pipeline
Dharmit Shah
 
Introduction to Kubernetes
Introduction to KubernetesIntroduction to Kubernetes
Introduction to Kubernetes
Dharmit Shah
 
Introduction to Containers
Introduction to ContainersIntroduction to Containers
Introduction to Containers
Dharmit Shah
 
Git push to build, test and scan your containers
Git push to build, test and scan your containersGit push to build, test and scan your containers
Git push to build, test and scan your containers
Dharmit Shah
 
Swarm mode
Swarm modeSwarm mode
Swarm mode
Dharmit Shah
 
Ansible in CI
Ansible in CIAnsible in CI
Ansible in CI
Dharmit Shah
 
Introduction to ansible
Introduction to ansibleIntroduction to ansible
Introduction to ansible
Dharmit Shah
 
Kubernetes
KubernetesKubernetes
Kubernetes
Dharmit Shah
 
Atomic Developer Bundle
Atomic Developer BundleAtomic Developer Bundle
Atomic Developer Bundle
Dharmit Shah
 
Docker tips & tricks
Docker  tips & tricksDocker  tips & tricks
Docker tips & tricks
Dharmit Shah
 
Introducing docker
Introducing dockerIntroducing docker
Introducing docker
Dharmit Shah
 
Rest apis with DRF
Rest apis with DRFRest apis with DRF
Rest apis with DRF
Dharmit Shah
 
Docker hands-on
Docker hands-onDocker hands-on
Docker hands-on
Dharmit Shah
 

More from Dharmit Shah (13)

Introducing CentOS container pipeline
Introducing CentOS container pipelineIntroducing CentOS container pipeline
Introducing CentOS container pipeline
 
Introduction to Kubernetes
Introduction to KubernetesIntroduction to Kubernetes
Introduction to Kubernetes
 
Introduction to Containers
Introduction to ContainersIntroduction to Containers
Introduction to Containers
 
Git push to build, test and scan your containers
Git push to build, test and scan your containersGit push to build, test and scan your containers
Git push to build, test and scan your containers
 
Swarm mode
Swarm modeSwarm mode
Swarm mode
 
Ansible in CI
Ansible in CIAnsible in CI
Ansible in CI
 
Introduction to ansible
Introduction to ansibleIntroduction to ansible
Introduction to ansible
 
Kubernetes
KubernetesKubernetes
Kubernetes
 
Atomic Developer Bundle
Atomic Developer BundleAtomic Developer Bundle
Atomic Developer Bundle
 
Docker tips & tricks
Docker  tips & tricksDocker  tips & tricks
Docker tips & tricks
 
Introducing docker
Introducing dockerIntroducing docker
Introducing docker
 
Rest apis with DRF
Rest apis with DRFRest apis with DRF
Rest apis with DRF
 
Docker hands-on
Docker hands-onDocker hands-on
Docker hands-on
 

Recently uploaded

A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024
Intelisync
 
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3
FREE A4 Cyber Security Awareness  Posters-Social Engineering part 3FREE A4 Cyber Security Awareness  Posters-Social Engineering part 3
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3
Data Hops
 
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframeDigital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Precisely
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
saastr
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Alpen-Adria-Universität
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
Jakub Marek
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
Jason Packer
 
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
Edge AI and Vision Alliance
 
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
saastr
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
Zilliz
 
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation TechniquesWeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
Postman
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
Tatiana Kojar
 
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
alexjohnson7307
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Tosin Akinosho
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Pixlogix Infotech
 
dbms calicut university B. sc Cs 4th sem.pdf
dbms  calicut university B. sc Cs 4th sem.pdfdbms  calicut university B. sc Cs 4th sem.pdf
dbms calicut university B. sc Cs 4th sem.pdf
Shinana2
 
Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |
AstuteBusiness
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
MichaelKnudsen27
 

Recently uploaded (20)

A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024
 
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3
FREE A4 Cyber Security Awareness  Posters-Social Engineering part 3FREE A4 Cyber Security Awareness  Posters-Social Engineering part 3
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3
 
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframeDigital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
 
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
 
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
 
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation TechniquesWeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
 
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
 
dbms calicut university B. sc Cs 4th sem.pdf
dbms  calicut university B. sc Cs 4th sem.pdfdbms  calicut university B. sc Cs 4th sem.pdf
dbms calicut university B. sc Cs 4th sem.pdf
 
Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
 

Python in Industry

  • 2. GOAL To make you aware of awesome career options for Python Programmers!
  • 3. Topics ● Who uses Python? How do they use Python? ● What kind of problems does Python help solve? ● What are different career options for a Python programmer? ● How to become a better Python programmer?
  • 4. Who am I? ● Developer at Red Hat ● Working on open source projects that are built using Python & Golang ● I organize and speak at various Meetups in Ahmedabad ○ Docker ○ Ansible ○ Kubernetes ○ DigitalOcean ● Firm believer in lifelong learning
  • 5. Brief intro to Python
  • 6. History of Python ● Developed by Guido van Rossum in late 1980s ● Named after a TV show called “Monty Python” ● Python interpreter developed using C language ● Open source - so you can contribute to it as well!
  • 7. Which organizations use Python? ● Red Hat ● YouTube ● Instagram, Facebook ● NASA ● Google ● Microsoft ● ...many more
  • 8. How do organizations use Python? ● Web framework for backend ● Data analysis (scientific and numeric computing) ● Machine learning & Artificial Intelligence ● Automating the boring tasks ● Configuration management ● Web Scraping ● Embedded systems
  • 10. What is a framework and why use it? ● Framework is a collection of code that makes it easier to develop applications ● Web framework makes it easy to write, scale and maintain web applications ● They provide features like: ○ URL routing ○ Database manipulation ○ Security ○ Session control ● Different frameworks have different set of features
  • 11. django (https://www.djangoproject.com/) ● Most popular web framework of Python ● Provides a lot of features to develop websites; probably most feature-rich! ● Works with number of databases using ORM (no need to learn SQL!) ● But doesn’t work so well with NoSQL ● Has a huge community of developers using it ● Extensive documentation available online!
  • 12. Flask (http://flask.pocoo.org) ● A minimalistic framework ● Very easy to get started with as a beginner ● Doesn’t follow batteries included approach of django ● Excellent online documentation and great community of developers
  • 13. Few other frameworks ● Bottle (http://bottlepy.org/docs/dev/index.html) ● Pyramid (http://www.pylonsproject.org/projects/pyramid/about) ● Falcon (https://falconframework.org/)
  • 15. What is Data Analysis? ● Process of producing meaningful information from a big (huge?) chunk of data ● Encompasses various other domains: ○ Data Mining ○ Business Intelligence ○ Predictive Analysis, etc. ● Closely related to Data Visualization ● Helps make decisions that might change the future!
  • 16. SciPy Ecosystem (https://www.scipy.org/index.html) ● An ecosystem of opensource software for maths, science & engineering ● NumPy ○ Package for numerical computation. ○ Helps define numerical arrays and matrices ○ Perform operations on arrays & matrices ● SciPy library ○ Collection of numerical algorithms and domain-specific toolboxes ○ Signal processing, optimization, statistics and more
  • 17. SciPy Ecosystem (contd..) ● Matplotlib ○ Popular plotting package ○ Helps plot 2D and basic 3D plots ● Pandas: provides high-performance, easy to use data structures ● scikit-image: collection of algorithms for image processing ● scikit-learn: collection of algorithms for machine learning ● IPython: an alternate interface to interact with Python interpreter
  • 18. Data Analysis ● Data is continuously increasing! ● Making sense of data is a hot skill ● People from varying educational background are picking it up! ● Jobs & opportunities up for grabs! ● Plenty of MOOC (massive open online course) available
  • 20. What is ML and AI? ● Ability of computers to learn without being programmed! ● Ability to perform data driven decisions ● Significant overlap with Data Mining ● ML focuses on prediction, based on known properties ● Data Mining focuses on the discovery of (previously) unknown properties
  • 21. Frameworks and libraries ● Mostly the same as the ones we covered in Data Analysis ● It’s about how we use those libraries ● Also, TensorFlow
  • 23. A book! ● Automating tasks that would otherwise take hours if done manually ● Great book titled “Automate the Boring Stuff with Python” ○ Search for text in a file or across multiple files ○ Create, update, move, and rename files and folders ○ Search the Web and download online content ○ Update and format data in Excel spreadsheets of any size ○ Split, merge, watermark, and encrypt PDFs ○ Send reminder emails and text notifications ○ Fill out online forms ● https://automatetheboringstuff.com/ (free to read online!)
  • 25. Python and Embedded systems ● Steadily increasing adaption ● Boards ○ MicroPython ○ Raspberry Pi ○ Arduino ● Lots and lots of documentation and tutorials available online!
  • 26. Few projects ● Motion sensor with alarm ● Home automation system ● Use Lego toys to make robotic cars ● Send board to space (PITS : Pi In The Sky) ● ...many, many more!
  • 28. What is it? ● Process of extracting data from websites ● Data from websites is downloaded for later analysis ● This data is then extracted ● The extracted content may be parsed, searched, reformatted, etc.
  • 29. Python tools for scraping ● BeautifulSoup ● Mechanize ● Scrapemark ● Scrapy
  • 30. What else can be done with Python? ● Chatbots ● Blockchain ● Configuration Management tools ● Desktop and mobile applications
  • 32. ● Developer ○ Backend developer ○ Full Stack developer ● System Administrator ● Data Scientist ● Many more specialized roles!
  • 33. How to get better at Python?
  • 34. Talk is cheap, write some code! ● Participate in open source projects ● Read more Python code and then write more ● Subscribe to newsletters ○ Python Weekly ○ Import Python ○ Pycoder’s Weekly ○ Full Stack Python ● Read and learn from ton of free online material about Python ● Find a mentor if you can