Python is a well-established in the web, scientific and engineering programming and is the platform for high-traffic sites like YouTube. Python has been used for scientific computing in government, academia, and industry for at least a decade. "NASA’s Jet Propulsion Laboratory uses it for interfacing Fortran/C++ libraries for planning and visualization of spacecraft trajectories."
This hands-on Python for Signal and Image Processing workshop is for engineers and scientists want to develop systems, applications, and algorithms for real-life problems. Basic Prior knowledge of Python is not required however some programming knowledge (including MatLab) is. The workshop will target basic understanding of Python programming, data handling, libraries and signal and image processing.
This hands-on Python for Signal and Image Processing workshop is for engineers and scientists want to develop systems, applications, and algorithms for real-life problems. Basic Prior knowledge of Python is not required however some programming knowledge (including MatLab) is. The workshop will target basic understanding of Python programming, data handling, libraries and signal and image processing.
Five Days Workshop:Python Programming for
Engineers, Scientists and Analysts
UCERD Gathering Intellectuals Fostering Innovations
Unal Center of Educaiton Research & Development
Unal Center of Educaiton Research & Development
UCERD Rawalpindi
Supercomputing Center
UCERD Murree
Day 1
Introduction to Python (1)
Past present and future of Python language.
The Python Environments
Python for different processing technology. Mobile Processor – Supercomputers
Python Data Types
Working with Data Structures
Working with Modules
Hands On Practice –
UCERD HPC Cluster
Google Colab
Day 2
Introduction to Python 2
Program Structure
• Statements, Comments, Joining Lines, Indentation, Operators, Operator Precedence, If Statements, Evaluating Variables, While Loops, For Loops, Tuple Assignment with For, Loops, Pass, And, Or, and Not
Functions
Exception Handling
Built-in Functions and Modules
Hands-on Lab Exercises
Day 3
Working with Files
Python Classes
Introduction to Scientific Python SciPy, NumPy, Pandas.
Data Visualization and Plotting
Hands-on Data Analysis
Day 4
Python programming for Embedded Systems
Programming Raspberry Pi and Arduino
Interfacing and Communication with external World
Serial Port, Parallel Port, Analog Sensing etc.
Day 5
Introduction to Computer Vision
Introduction to Machine Learning
Introduction to Deep Learning
Deep learning for Distributed Systems (Supercomputers)
Hands-on Session
Introduction to Python (1)
Past present and future of Python language.
The Python Environments
Python for different processing technology. Mobile Processor – Supercomputers
Python Data Types
Working with Data Structures
Working with Modules
Hands On Practice –
UCERD HPC Cluster
Google Colab
Day 2
Introduction to Python 2
Program Structure
• Statements, Comments, Joining Lines, Indentation, Operators, Operator Precedence, If Statements, Evaluating Variables, While Loops, For Loops, Tuple Assignment with For, Loops, Pass, And, Or, and Not
Functions
Exception Handling
Built-in Functions and Modules
Hands-on Lab Exercises
Day 3
Working with Files
Python Classes
Introduction to Scientific Python SciPy, NumPy, Pandas.
Data Visualization and Plotting
Hands-on Data Analysis
Day 4
Python programming for Embedded Systems
Programming Raspberry Pi and Arduino
Interfacing and Communication with external World
Serial Port, Parallel Port, Analog Sensing etc.
Day 5
Introduction to Computer Vision
Introduction to Machine Learning
Introduction to Deep Learning
Deep learning for Distributed Systems (Supercomputers)
Hands-on Session
Dr. Tassadaq Hussain.
He is a permanent faculty member at, Riphah International University.
He did his Ph.D. from Barcelona-tech Spain, in collaboration with Barcelona Supercomputing Center and Microsoft Research Center.
He is a member of HiPEAC: European Network on High Performance and Embedded Architecture and Compilation, Barcelona Supercomputing Center and Microsoft ResearchCentre Spain.
Until January 2020, he had more than 16 years of industrial experience including, Barcelona Supercomputing Centre Spain, Infineon technology France, Microsoft Research Cambridge, PLDA Italia, IBM Zurich Switzerland, and REPSOL Spain. He has published more than 70 international publications and filed 12 patents.
Tassadaq's main research lines are Machine Learning, Parallel Programming, Heterogeneous Multi-core Architectures, Single board Computers, Embedded Computer Vision, Runtime Resource Aware Architectures, Software Defined Radio and Supercomputing for Artificial Intelligence and Scientific Computing.
www.tassadaq.ucerd.com
He is a permanent faculty member at, Riphah International University.
He did his Ph.D. from Barcelona-tech Spain, in collaboration with Barcelona Supercomputing Center and Microsoft Research Center.
He is a member of HiPEAC: European Network on High Performance and Embedded Architecture and Compilation, Barcelona Supercomputing Center and Microsoft ResearchCentre Spain.
Until January 2020, he had more than 16 years of industrial experience including, Barcelona Supercomputing Centre Spain, Infineon technology France, Microsoft Research Cambridge, PLDA Italia, IBM Zurich Switzerland, and REPSOL Spain. He has published more than 70 international publications and filed 12 patents.
Tassadaq's main research lines are Machine Learning, Parallel Programming, Heterogeneous Multi-core Architectures, Single board Computers, Embedded Computer Vision, Runtime Resource Aware Architectures, Software Defined Radio and Supercomputing for Artificial Intelligence and Scientific Computing.
www.tassadaq.ucerd.com
