
Online or onsite, instructor-led live Python training courses demonstrate through hands-on practice various aspects of the Python programming language. Some of the topics covered include the fundamentals of Python programming, advanced Python programming, Python for test automation, Python scripting and automation, and Python for Data Analysis and Big Data applications in areas such as Finance, Banking and Insurance.
NobleProg Python training courses also cover beginning and advanced courses in the use of Python libraries and frameworks for Machine Learning and Deep Learning.
Python training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Python training can be carried out locally on customer premises in Sri Lanka or in NobleProg corporate training centers in Sri Lanka.
NobleProg -- Your Local Training Provider
Testimonials
I preferred the exercise and learning about the nooks and crannies of Python.
Connor Brierley-Green
Course: Python Programming
Joey has an infectious enthusiasm about programming. And he was very good at adapting to our needs and interests on the fly.
Randy Enkin
Course: Python Programming
Many examples made me easy to understand.
Lingmin Cao
Course: Python Programming
Fact that customization was taken seriously.
jurgen linsen
Course: Python Programming
As I was the only participant the training could be adapted to my needs.
Kevin THIERRY
Course: Web Development with Web2Py
I did like the exercises.
Office for National Statistics
Course: Natural Language Processing with Python
I liked the helpful and very kind.
Natalia Machrowicz
Course: Python Programming
We did practical exercises (the scripts we wrote can be used in our everyday work). It made the course very interesting. I also liked the way the trainer shared his knowledge. He did it in a very accessible way.
Malwina Sawa
Course: Python Programming
Very good approach to memorize/repeat the key topics. Very nice “warm-up” exercises.
Course: Python Programming
* Enjoyable exercises. * Quickly moved into more advanced topics. * Trainer was friendly and easy to get on with. * Customized course for needs of team.
Matthew Lucas
Course: Python Programming
I enjoyed the felixibility to add specific topics into the course / lessons.
Marc Ammann
Course: Python Programming
In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.
Sacha Nandlall
Course: Python for Advanced Machine Learning
I liked the customized, in-house file processing and data analysis.
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
The case studies helped us understand how we can apply Python in the industry. Really appreciated the trainer's help during the exercises.
Rajiv Dhingra - TCS
Course: Python Programming
As we are PHP developers, he understood the situation and allowed us to slowly map things between. I liked the examples and the humor he added.
Soumya Tyagi - TCS
Course: Python Programming
I enjoyed the that we have used our own data as examples.
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
the training is not presentation styled. We were coding with he trainer.
Bhutan Telecom
Course: Web Development with Django
I mostly enjoyed everything.
Thukten Dendup - Bhutan Telecom
Course: Web Development with Django
Its a new experience, a new framework and looking forward to do something using the lesson learnt in the classes.
Jigme - Bhutan Telecom
Course: Web Development with Django
I genuinely enjoyed the lots of labs and practices.
Vivian Feng - Destination Canada
Course: Data Analysis with SQL, Python and Spotfire
The exercises/labs were tailored to our own organizational needs.
Destination Canada
Course: Data Analysis with SQL, Python and Spotfire
I generally liked the subject matter.
Destination Canada
Course: Data Analysis with SQL, Python and Spotfire
The trainer was sharing real word experiences, it's nice to learn from real professional.
Fednot
Course: Python Programming
The trainer was excellent, He was always ready to answer my questions and share as much knowledge as he could.
Fahad Malalla - Tatweer Petroleum
Course: Advanced Python
1:1 very intensive but learnt a lot.
Karen Dyke - BT
Course: Python: Automate the Boring Stuff
I mostly enjoyed the subject.
Proximus
Course: Python Programming
The way the exercises were organized : all on own tempo and Antonio there to help you further.
Proximus
Course: Python Programming
I liked the sufficient and very detailed reading materials and examples (slides).
HC Consumer Finance Philippines, Inc.
Course: Python Programming
I genuinely liked the na.
HC Consumer Finance Philippines, Inc.
Course: Python Programming
What I like the most about the training is that everything in the course outline is something that will be useful for our projects.
Joanna Marie Escueta - Aarki, Inc.
Course: Python Programming
The overview/the recommendations
frddy de meersman - Proximus
Course: Python Programming
Labs
Proximus
Course: Python Programming
practice tasks
Pawel Kozikowski - GE Medical Systems Polska Sp. Zoo
Course: Python and Spark for Big Data (PySpark)
Recap of previous day, trainer very knowledgable in answering questions
Mateusz Jaros - GE Medical Systems Polska Sp. Zoo
Course: Python Programming
It gave me a broad overview of the possibilites
GE Medical Systems Polska Sp. Zoo
Course: Python Programming
really kind, good approach to trainees, helpful
GE Medical Systems Polska Sp. Zoo
Course: Python Programming
I like pace of the training. It was good and we were able to cover many aspects of programming language. Trainer was able to show many applications of Python in very informative way. Trainer sent to us many scripts and micro-programs for furher reference which is very useful. I like, that we started training with some technical remarks and setting up virtual environment.
Bartosz Rosiek - GE Medical Systems Polska Sp. Zoo
Course: Python Programming
I thought John was very knowledgeable and able to diseminate information in a very understandable way.
Crux Product Design
Course: Python Programming Fundamentals
John was a very friendly and knowledgeable trainer and was keen to adapt the course to our requests.
Crux Product Design
Course: Python Programming Fundamentals
Gaining a better understanding of object oriented programming as this is a key difference to programming in Matlab (which I am much more familiar with). The training should hopefully be very useful!
Crux Product Design
Course: Python Programming Fundamentals
knew his subject well
Albert JACOB - Proximus
Course: Python Programming
The exercises combined with the experienced help of the trainer
Proximus
Course: Python Programming
The fact that we could practice a lot. Even though for me being a newbe the pace was to fast and explanation too few. However, probably due to the mixed knowkedge level of the students attending the class.
Proximus
Course: Python Programming
Trainer obviously had a great holistic understanding of programming.
Crux Product Design
Course: Python Programming Fundamentals
the last day. generation part
Accenture Inc
Course: Python for Natural Language Generation
The topics referring to NLG. The team was able to learn something new in the end with topics that were interesting but it was only in the last day. There were also more hands on activities than slides which was good.
Accenture Inc
Course: Python for Natural Language Generation
I enjoyed the sentinal analysis/ data science aspect of the course.
Jake Hamilton - Scottish Government
Course: Python Programming
pace and explanations
Centric IT Solutions Lithuania
Course: Advanced Python
I like that it focuses more on the how-to of the different text summarization methods
Course: Text Summarization with Python
The trainer was great! If he would have more time I think we could have learned a lot more.
Zarim Jei Serrano - Cloudstaff Philippines, Inc.
Course: Python Programming Fundamentals
Very good approach to memorize/repeat the key topics. Very nice “warm-up” exercises.
Course: Python Programming
I like that it focuses more on the how-to of the different text summarization methods
Course: Text Summarization with Python
Python Course Outlines in Sri Lanka
- Perform data analysis using Python, R, and SQL.
- Create insights through data visualization with Tableau.
- Make data-driven decisions for business operations.
- Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
- Understand the features, core components, and architecture of Spark and Hadoop.
- Learn how to integrate Spark, Hadoop, and Python for big data processing.
- Explore the tools in the Spark ecosystem (Spark MlLib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
- Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
- Use Apache Mahout to scale machine learning algorithms.
- Set up the necessary environment to perform data analysis with SQL, Python, and Tableau.
- Understand the key concepts of software integration (data, servers, clients, APIs, endpoints, etc.).
- Get a refresher on the fundamentals of Python and SQL.
- Perform data pre-processing techniques in Python.
- Learn how to connect Python and SQL for data analysis.
- Create insightful data visualizations and charts with Tableau.
- Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
- Understand the key concepts, features, and benefits of the FARM stack.
- Learn how to build REST APIs with FastAPI.
- Learn how to design interactive applications with React.
- Develop, test, and deploy applications (front end and back end) using the FARM stack.
- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world cases.
- Use different tools and techniques for big data analysis using PySpark.
- Automating tasks by writing simple Python programs.
- Writing programs that can do text pattern recognition with "regular expressions".
- Programmatically generating and updating Excel spreadsheets.
- Parsing PDFs and Word documents.
- Crawling web sites and pulling information from online sources.
- Writing programs that send out email notifications.
- Use Python's debugging tools to quickly resolve bugs.
- Programmatically controlling the mouse and keyboard to click and type for you.
- Implement machine learning algorithms and techniques for solving complex problems.
- Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
- Push Python algorithms to their maximum potential.
- Use libraries and packages such as NumPy and Theano.
- Write readable and maintainable tests without the need for boilerplate code.
- Use the fixture model to write small tests.
- Scale tests up to complex functional testing for applications, packages, and libraries.
- Understand and apply PyTest features such as hooks, assert rewriting and plug-ins.
- Reduce test times by running tests in parallel and across multiple processors.
- Run tests in a continuous integration environment, together with other utilities such as tox, mock, coverage, unittest, doctest and Selenium.
- Use Python to test non-Python applications.
- Set up a real-time interactive dashboard for streaming live updating data.
- Build interactive dashboards using Python for data science solutions.
- Secure interactive dashboards with advanced authentication methods.
- Understand the fundamentals of the Python programming language
- Download, install and maintain the best development tools for creating financial applications in Python
- Select and utilize the most suitable Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate, deploy, and optimize a Python application
- Developers
- Analysts
- Quants
- Part lecture, part discussion, exercises and heavy hands-on practice
- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
- Install and configure packages for integrating Python and Excel.
- Read, write, and manipulate Excel files using Python.
- Call Python functions from Excel.
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
- Set up a development environment that includes all needed libraries, packages and frameworks.
- Create a desktop or server application whose user interface functions smoothly and is visually appealing.
- Implement various UI elements and effects, including widgets, charts, layers, etc. to achieve maximum effect in usability.
- Implement good UI design and code organization during the design and development phase.
- Test and debug the application.
- Install and configure a Python development environment.
- Understand the differences and similarities between Matlab and Python syntax.
- Use Python to obtain insights from various datasets.
- Convert existing Matlab applications to Python.
- Integrate Matlab and Python applications.
- Understand the fundamental concepts of deep learning.
- Learn the applications and uses of deep learning in telecom.
- Use Python, Keras, and TensorFlow to create deep learning models for telecom.
- Build their own deep learning customer churn prediction model using Python.
- Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
- Analyze data from sources such as Excel, CSV, JSON files and databases.
- Clean data to improve its usefulness before analyzing it.
- Perform simple statistical analysis.
- Generate reports that present the desired data in just the right format, from straight numbers to data visualizations.
- Gain valuable insight from data, including trends in performance, problematic areas.
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