NP Classroom - Thimphu

near Le Méridien , Chorten Lam, Thimphu, Bhutan, 11001

Set in Thimphu, this classroom is well located in Chorten Lam with all amenities and WiFi.

For Sales En...

NP Classroom - Paro

near Le Méridien Riverfront, thimphu hwy, Shaba, Paro, Bhutan, 12001

Set in Paro, this classroom is well located near Paro-Thimphu Highway around 4 km from the airport, and 7 km from Rinpung ...

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Django
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PyQt
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Kivy
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Tkinter
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Web2py
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SciPy
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Pandas

Explore Our Courses

Data Analytics with Python in Power BI

28 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at expert-level data analysts who wish to leverage Python's data analysis capabilities within Power BI, enhancing their ability to analyze and visualize data effectively. By the end of this training, participants will be able to:
  • Learn how Python can be integrated into Power BI for data analysis.
  • Use Python scripts to load, clean, and preprocess data within the Power BI environment.
  • Enhance data visualization capabilities by creating custom and interactive visualizations using Python.
  • Acquire advanced data analysis skills using Python.
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Cybersecurity with Python

14 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at experienced developers who wish to gain a comprehensive understanding of Python programming and its applications in cybersecurity. By the end of this training, participants will be able to:
  • Use Python programming for defensive cybersecurity.
  • Understand and use Python for ethical offensive techniques and digital forensics tasks.
  • Recognize legal and ethical considerations surrounding offensive cybersecurity and vulnerability disclosure.
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Data Analytics with Tableau, Python, R, and SQL

35 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at data analysts and anyone who is interested to learn how to use and integrate Tableau, Python, R, and SQL for data visualization and analysis. By the end of this training, participants will be able to:
  • Perform data analysis using Python, R, and SQL.
  • Create insights through data visualization with Tableau.
  • Make data-driven decisions for business operations.
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Python, Spark, and Hadoop for Big Data

21 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at developers who wish to use and integrate Spark, Hadoop, and Python to process, analyze, and transform large and complex data sets. By the end of this training, participants will be able to:
  • 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.
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ROS for Mobile Robots using Python

21 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at beginner-level to intermediate-level and potentially advanced-level robotics developers who wish to learn how to use ROS to program mobile robots using Python.By the end of this training, participants will be able to:
  • Set up a development environment that includes ROS, Python, and a mobile robot platform.
  • Create and run ROS nodes, topics, services, and actions using Python.
  • Use ROS tools and utilities to monitor and debug ROS applications.
  • Use ROS packages and libraries to perform common tasks for mobile robots.
  • Integrate ROS with other frameworks and tools.
  • Troubleshooting and debugging ROS applications.
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Data Analysis with SQL, Python, and Tableau

14 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at data scientists and developers who wish to use and integrate SQL, Python, and Tableau to perform complex data analysis, processing, and visualization. By the end of this training, participants will be able to:
  • 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.
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FARM (FastAPI, React, and MongoDB) Full Stack Development

14 Hours
This instructor-led, live training in (online or onsite) is aimed at developers who wish to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications. By the end of this training, participants will be able to:
  • 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.
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Python Programming - 4 days

28 Hours
This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages. The course can be delivered using the latest Python version 3.x with practical exercises making use of the full power. This course can be delivered on any operating system (all flavours of UNIX, including Linux and Mac OS X, as well as Microsoft Windows). The practical exercises constitute about 70% of the course time, and around 30% are demonstrations and presentations. Discussions and questions can be asked throughout the course. Note: the training can be tailored to specific needs upon prior request ahead of the proposed course date.
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Advanced Python - 4 Days

28 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at developers who wish to learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, data analysis and visualization, UI programming and maintenance scripting.
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Python and Spark for Big Data (PySpark)

21 Hours
In this instructor-led, live training in Bhutan, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises. By the end of this training, participants will be able to:
  • 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.
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Python Programming Fundamentals

14 Hours
This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.
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Python in Data Science

35 Hours
The training course will help the participants prepare for Web Application Development using Python Programming with Data Analytics. Such data visualization is a great tool for Top Management in decision making.
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Machine Learning with Python – 2 Days

14 Hours
The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
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Python: Automate the Boring Stuff

14 Hours
This instructor-led, live training in Bhutan is based on the popular book, "Automate the Boring Stuff with Python", by Al Sweigart. It is aimed at beginners and covers essential Python programming concepts through practical, hands-on exercises and discussions. The focus is on learning to write code to dramatically increase office productivity. By the end of this training, participants will know how to program in Python and apply this new skill for:
  • 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.
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Advanced Machine Learning with Python

21 Hours
In this instructor-led, live training in Bhutan, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data. By the end of this training, participants will be able to:
  • 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.
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Data Analysis with Python, Pandas and Numpy

14 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.By the end of this training, participants will be able to:
  • Set up a development environment that includes Python, Pandas, and NumPy.
  • Create a data analysis application using Pandas and NumPy.
  • Perform advanced data wrangling, sorting, and filtering operations.
  • Conduct aggregate operations and analyze time series data.
  • Visualize data using Matplotlib and other visualization libraries.
  • Debug and optimize their data analysis code.
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Unit Testing with Python

21 Hours
In this instructor-led, live training in Bhutan, participants will learn how to use PyTest to write short, maintainable tests that are elegant, expressive and readable.  By the end of this training, participants will be able to:
  • 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.
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Python with Plotly and Dash

14 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at data analysts who wish to build analytic applications using Python with Plotly and Dash. By the end of this training, participants will be able to:
  • 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.
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Machine Learning with Python – 4 Days

28 Hours
The aim of this course is to provide general proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
Read more...

Natural Language Processing (NLP) with Python

28 Hours
This course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.
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Python Programming for Finance

35 Hours
Python is a programming language that has gained huge popularity in the financial industry. Adopted by the largest investment banks and hedge funds, it is being used to build a wide range of financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a number of specific finance related problems. By the end of this training, participants will be able to:
  • 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
Audience
  • Developers
  • Analysts
  • Quants
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Note
  • 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.
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Python for Geographic Information System (GIS)

21 Hours
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics. The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers. This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.
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Introduction to Data Science and AI using Python

35 Hours
This is a 5 day introduction to Data Science and Artificial Intelligence (AI). The course is delivered with examples and exercises using Python 
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Applied AI from Scratch in Python

28 Hours
This is a 4 day course introducing AI and it's application using the Python programming language. There is an option to have an additional day to undertake an AI project on completion of this course. 
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Test Automation with Selenium and Python

14 Hours
In this instructor-led, live training in Bhutan participants combine the power of Python with Selenium to automate the testing of a sample web application. By combining theory with practice in a live lab environment, participants will gain the knowledge and practice needed to automate their own web testing projects using Python and Selenium.
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Python for Excel

14 Hours
In this instructor-led, live training in Bhutan (onsite or remote), participants will learn how to combine the capabilities of Python and Excel. By the end of this training, participants will be able to:
  • Install and configure packages for integrating Python and Excel.
  • Read, write, and manipulate Excel files using Python.
  • Call Python functions from Excel.
Read more...

Data Analysis with SQL, Python and Spotfire

14 Hours
In this instructor-led, live training in Bhutan, participants will learn three different approaches for accessing, analyzing and visualizing data. We start with an introduction to RDMS databases; the focus will be on accessing and querying an Oracle database using the SQL language. Then we look at strategies for accessing an RDMS database programmatically using the Python language. Finally, we look at how to visualize and present data graphically using TIBCO Spotfire.  Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
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BDD with Python and Behave

7 Hours
This instructor-led, live training in Bhutan begins with a discussion of BDD and how the Behave framework can be used to carry out BDD testing for web applications. Participants are given ample opportunity to interact with the instructor and peers while implementing the concepts and tactics learned in this hands-on, practice-based lab environment. By the end of this training, participants will have a firm understanding of BDD and Behave, as well as the necessary practice to implement these techniques and tools in real-world test scenarios.
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GUI Programming with Python and PyQt

21 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at persons who wish to program a visually attractive software application using Python and the Qt UI framework. By the end of this training, participants will be able to:
  • 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.
Read more...

Python for Matlab Users

14 Hours
This instructor-led, live training in Bhutan (online or onsite) is aimed at Matlab users who wish to explore and or transition to Python for data analytics and visualization. By the end of this training, participants will be able to:
  • 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.
Read more...

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Testimonials (50)

examples and exercises

Kamil
Course - Introduction to Data Science and AI using Python

Machine Translated

The course is very interesting being the main focus nowdays

mohamed taher - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

Ahmed was very interactive and didn’t mind answering any kind of questions Well presentation and smooth flow of the course

Mohamed Ghowaiba - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

Helpful and good listener .. interactive

Ahmed El Kholy - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

That it was applying real company data. Trainer had a very good approach by making trainees participate and compete

Jimena Esquivel - Zakład Usługowy Hakoman Andrzej Cybulski
Course - Applied AI from Scratch in Python

The trainer was a professional in the subject field and related theory with application excellently

Fahad Malalla - Tatweer Petroleum
Course - Applied AI from Scratch in Python

Very interactive with various examples, with a good progression in complexity between the start and the end of the training.

Jenny - Andheo
Course - GPU Programming with CUDA and Python

examples based on our data

Witold - P4 Sp. z o.o.
Course - Deep Learning for Telecom (with Python)

code examples:-)

Marcin - P4 Sp. z o.o.
Course - Deep Learning for Telecom (with Python)

I liked that the instructor had many pre-written scripts to show off many different aspects of ML and AI. I really enjoyed being able to see live demos of so many ways ML and AI is being used. Much of what we covered was cutting edge technology that is still in its early stages of development.

Matthew Pepper - Motorola Solutions
Course - Deep Learning for Telecom (with Python)

The colab notebooks we get to keep

Palmer Greer - Motorola Solutions
Course - Deep Learning for Telecom (with Python)

The clarity with which it was presented

John McLemore - Motorola Solutions
Course - Deep Learning for Telecom (with Python)

Practical examples and wider context given.

James - Mitsubishi Electric R&D Centre Europe BV (MERCE-UK)
Course - IoT Programming with Python

The trainer showed that he has a good understanding of the subject.

Marino - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days

It was a great intro to ML!! I liked the whole thing, really. The organization was perfect. The right amount of time for lectures/ demos and just us playing around. Lots of topics were touched, just at the right level. He was also very good at keeping us super engaged, even without any camera being on.

Zsolt - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days

Clarity of explanation and knowledgeable response to questions.

Harish - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days

The knowledge of the trainer was very high and the material was well prepared and organised.

Otilia - TCMT
Course - Machine Learning with Python – 2 Days

I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.

Jenna - TCMT
Course - Machine Learning with Python – 2 Days

Interesting knowledge

Gabriel - MINDEF
Course - Machine Learning with Python – 4 Days

The trainer was a practitioner with a lot of experience and had a very good knowledge of the material.

Witold Iwaniec - City of Calgary
Course - Machine Learning with Python – 4 Days

The trainer because he could handle almost every subject and situation.

Florin Babes - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days

The manner in which the trainer explained the concepts, his positive and welcoming attitude and the real-world examples provided for each exercise.

Ovidiu Calita - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days

Very good training session with nice documentation and exercises and Kristian did it like a professional he is.

Adrian Boulescu - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days

The accesibilit of the trainer and the ability to communicate very effective,

Ciprian Ilie - Institutul National de Sanatate Publica
Course - Programming for Biologists

I'm looking forward to having a training again with Any, he was really good, I'm just a GIS guy, but Any made everything clear to me, he explained complex processes in layman's terms. Keep it up, thank you.

Lwazi Qhingana - South African National Roads Agency (SANRAL) SOC Ltd
Course - Python for Geographic Information System (GIS)

I really enjoyed the training. I found all modules to be applicable to problems that I am trying to solve at work. The integration of the training with jupyter notebooks was really impressive.

Mark Firmin - Environment and Climate Change Canada
Course - Python for Geographic Information System (GIS)

Content and example. virtual computer is helpful (my version of anaconda does not have Dash library yet)

Jennifer Ni - AllianceBernstein
Course - Python with Plotly and Dash

I did like that there was a prominent hands on component. Kritika was very personable, knowledgeable, and helpful.

Noah Zarr - AllianceBernstein
Course - Python with Plotly and Dash

The course was straight forward, intuitive, easy to follow, the exercises covered the subjects discussed beforehand.

Alexandru - BRD
Course - Python Programming Fundamentals

The knowledgeability.

Dan Nohai - BRD
Course - Python Programming Fundamentals

Abhi is a really well skilled developer with a lost of knowledge and also has the necessary skills of a trainer that i really liked.

Andrei - BRD
Course - Python Programming Fundamentals

I liked that all the notions regarding the Python language were explained in detail and that we were allowed to solve some exercises on our own, following which the trainer would explain them to us and offer various solutions. A very good course!

Scanteie Ana - BRD
Course - Python Programming Fundamentals

Explicatiile legate de faptul ca exista multe posibilitati de programare si existenta functiilor.

Adriana - Siemens
Course - Python Programming Fundamentals

Everything, great trainer.

Michał Rawicki
Course - Unit Testing with Python

Machine Translated

Expertise of the trainer, even if we asked very precise questions about specific topic, he was able to provide really meaningful and valuable for us questions. He has designed agenda of the training according to our needs and requests.

Filip - Orange Szkolenia Sp. z o.o.
Course - Unit Testing with Python

I loved summaries

Martyna - Orange Szkolenia Sp. z o.o.
Course - Unit Testing with Python

Materials Trainer

Zakar Abid - TII
Course - Unit Testing with Python

Did hands on exercise. Walked through the code. Explained everything very well

Steve Thomas - TII
Course - Unit Testing with Python

In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.

Sacha Nandlall
Course - Python for Advanced Machine Learning

Lots of examples of different cases, and materials which will be useful in future as I try to apply lessons to my work applications. Also, it was great that there were tasks to do at home in between lessons, as it gives the opportunity to pick up on the parts of the previous lesson, with which I struggled. If I had a question during a lesson, the teacher would gladly help and explain the problem, and the teacher had good expertise on all questions that were asked.

Raivis - Gravity Team
Course - Python: Automate the Boring Stuff

1:1 very intensive but learnt a lot.

Karen Dyke - BT
Course - Python: Automate the Boring Stuff

Trainer was very knowlegable and very open to feedback on what pace to go through the content and the topics we covered. I gained alot from the training and feel like I now have a good grasp of image manipulation and some techniques for building a good training set for an image classification problem.

Anthea King - WesCEF
Course - Computer Vision with Python

very comprehensive in regards to doing data analysis using python

Mervin Lau - MINDEF
Course - Python for Data Analysis

Trainer was very patient with helping us resolve problems that we had faced as well as clarifying our doubts.

Chua Wei Zhi - MINDEF
Course - Python for Data Analysis

clear explanation with adequate examples.

Raphael Reynold - MINDEF
Course - Python for Data Analysis

Patience of the trainer while making sure everyone understand the lesson

Yeo Yu Xin - Ministry of Defence, Singapore
Course - Python for Data Analysis

Knowledge, substantive content, contact with others, willingness to help even with trivial problems, ability to interest listeners.

Michał
Course - Python for Excel

Machine Translated

Trainer was accommodative. And actually quite encouraging for me to take up the course.

Grace Goh - DBS Bank Ltd
Course - Python in Data Science

Plenty of examples - and the trainer willing to bend backwards to help us with topics we were weaker in.

Wei Lit Teoh - HP Singapore (Private) Ltd.
Course - Advanced Python - 4 Days

Lots of exercises

Fanny Stauffer - UCB Pharma S.A.
Course - Advanced Python - 4 Days
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