Explore Our Courses

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 Colombia (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 Colombia, 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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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 Colombia 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 Colombia, 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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Unit Testing with Python

 21 Hours
In this instructor-led, live training in Colombia, 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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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.
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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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Test Automation with Selenium and Python

 14 Hours
In this instructor-led, live training in Colombia 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 Colombia (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.
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BDD with Python and Behave

 7 Hours
This instructor-led, live training in Colombia 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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Learn Object-Oriented Programming with Python

 14 Hours
Object-Oriented Programming (OOP) is a programming paradigm based around the concept of objects. OOP is more data-focused rather than logic-focused. Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn how to get started with Object-Oriented Programming using Python. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of Object-Oriented Programming
  • Understand the OOP syntax in Python
  • Write their own object-oriented program in Python
Audience
  • Beginners who would like to learn about Object-Oriented Programming
  • Developers interested in learning OOP in Python
  • Python programmers interested in learning OOP
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Deep Learning for Telecom (with Python)

 28 Hours
In this instructor-led, live training in Colombia, participants will learn how to implement deep learning models for telecom using Python as they step through the creation of a deep learning credit risk model. By the end of this training, participants will be able to:
  • 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.
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Programming for Biologists

 28 Hours
This is a practical course, which shows why programming is a powerful tool in the context of solving biological problems. During the course participants will be taught the Python programming language, a language widely considered both powerful as well as easy to use. This course might be considered as a demonstration how bioinformatics improves biologists lives. The course is designed and aimed for people without computer science background who want to learn to program. This course is suited for:
  • Researchers dealing with biological data.
  • Scientists who would like to learn how to automate everyday tasks and analyse data.
  • Managers who want to learn how programming improves workflows and conducting projects.
By the end of the course, participants will be able to write short programs, which will allow them to manipulate, analyse and deal with biological data and present results in a graphical format.
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Python for Natural Language Generation

 21 Hours
Natural language generation (NLG) refers to the production of natural language text or speech by a computer. In this instructor-led, live training, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content. By the end of this training, participants will be able to:
  • Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting
  • Select and organize source content, plan sentences, and prepare a system for automatic generation of original content
  • Understand the NLG pipeline and apply the right techniques at each stage
  • Understand the architecture of a Natural Language Generation (NLG) system
  • Implement the most suitable algorithms and models for analysis and ordering
  • Pull data from publicly available data sources as well as curated databases to use as material for generated text
  • Replace manual and laborious writing processes with computer-generated, automated content creation
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Natural Language Processing (NLP) with Deep Dive in Python and NLTK

 35 Hours
By the end of the training the delegates are expected to be sufficiently equipped with the essential python concepts and should be able to sufficiently use NLTK to implement most of the NLP and ML based operations. The training is aimed at giving not just an executional knowledge but also the logical and operational knowledge of the technology therein.  
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Machine Learning for Banking (with Python)

 21 Hours
Machine Learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Python is a programming language famous for its clear syntax and readability. It offers an excellent collection of well-tested libraries and techniques for developing machine learning applications. In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the banking industry. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of team projects. Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Text Summarization with Python

 14 Hours
In Python Machine Learning, the Text Summarization feature is able to read the input text and produce a text summary. This capability is available from the command-line or as a Python API/Library. One exciting application is the rapid creation of executive summaries; this is particularly useful for organizations that need to review large bodies of text data before generating reports and presentations. In this instructor-led, live training, participants will learn to use Python to create a simple application that auto-generates a summary of input text. By the end of this training, participants will be able to:
  • Use a command-line tool that summarizes text.
  • Design and create Text Summarization code using Python libraries.
  • Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17
Audience
  • Developers
  • Data Scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Machine Learning for Finance (with Python)

 21 Hours
Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Python is a programming language famous for its clear syntax and readability. It offers an excellent collection of well-tested libraries and techniques for developing machine learning applications. In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the finance industry. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of team projects. By the end of this training, participants will be able to:
  • Understand the fundamental concepts in machine learning
  • Learn the applications and uses of machine learning in finance
  • Develop their own algorithmic trading strategy using machine learning with Python
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Analyzing Financial Data with Python

 35 Hours
Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn how to use Python for quantitative finance. By the end of this training, participants will be able to:
  • Understand the fundamentals of Python programming
  • Use Python for financial applications including implementing mathematical techniques, stochastics, and statistics
  • Implement financial algorithms using performance Python
Audience
  • Developers
  • Quantitative analysts
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Computer Vision with Python

 14 Hours
Computer Vision is a field that involves automatically extracting, analyzing, and understanding useful information from digital media. Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn the basics of Computer Vision as they step through the creation of set of simple Computer Vision application using Python. By the end of this training, participants will be able to:
  • Understand the basics of Computer Vision
  • Use Python to implement Computer Vision tasks
  • Build their own face, object, and motion detection systems
Audience
  • Python programmers interested in Computer Vision
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Deep Learning for Banking (with Python)

 28 Hours
Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. Python is a high-level programming language famous for its clear syntax and code readability. In this instructor-led, live training, participants will learn how to implement deep learning models for banking using Python as they step through the creation of a deep learning credit risk model. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of deep learning
  • Learn the applications and uses of deep learning in banking
  • Use Python, Keras, and TensorFlow to create deep learning models for banking
  • Build their own deep learning credit risk model using Python
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Deep Learning for Finance (with Python)

 28 Hours
Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. Python is a high-level programming language famous for its clear syntax and code readability. In this instructor-led, live training, participants will learn how to implement deep learning models for finance using Python as they step through the creation of a deep learning stock price prediction model. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of deep learning
  • Learn the applications and uses of deep learning in finance
  • Use Python, Keras, and TensorFlow to create deep learning models for finance
  • Build their own deep learning stock price prediction model using Python
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Building Microservices with Python

 7 Hours
Microservices refer to an application architecture style that promotes the use of independent, self-contained programs. Python is a dynamic high-level programming language that is ideal for both scripting as welll as application development. Python's expansive library of open source tools and frameworks make it a practical choice for building microservices. In this instructor-led, live training, participants will learn the fundamentals of microservices as they step through the creation of a microservice using Python. By the end of this training, participants will be able to:
  • Understand the basics of building microservices
  • Learn how to use Python to build microservices
  • Learn how to use Docker to deploy Python based microservices
Audience
  • Developers
  • Programmers
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Data Analysis with Tableau and Python

 14 Hours
Tableau is a business intelligence and data visualization tool. Python is a widely used programming language which provides support for a wide variety of statistical and machine learning techniques. Tableau's data visualization power and Python's machine learning capabilities, when combined, help developers rapidly build advanced data analytics applications for various business use cases. In this instructor-led, live training, participants will learn how to combine Tableau and Python to carry out advanced analytics. Integration of Tableau and Python will be done via the TabPy API. By the end of this training, participants will be able to:
  • Integrate Tableau and Python using TabPy API
  • Use the integration of Tableau and Python to analyze complex business scenarios with few lines of Python code
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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IoT Programming with Python

 14 Hours
Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, allowing them to communicate with each other and exchange data via network communications, cloud computing, and data capture. Python is a high-level programming language recommended for IoT due to its clear syntax and large community support. In this instructor-led, live training, participants will learn how to program IoT solutions with Python. By the end of this training, participants will be able to:
  • Understand the fundamentals of IoT architecture
  • Learn the basics of using Raspberry Pi
  • Install and configure Python on Raspberry Pi
  • Learn the benefits of using Python in programming IoT systems
  • Build, test, deploy, and troubleshoot an IoT system using Python and Raspberry Pi
Audience
  • Developers
  • Engineers
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Note
  • To request a customized training for this course, please contact us to arrange.
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Building Chatbots in Python

 21 Hours
ChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions. In this instructor-led, live training, participants will learn how to build chatbots in Python. By the end of this training, participants will be able to:
  • Understand the fundamentals of building chatbots
  • Build, test, deploy, and troubleshoot various chatbots using Python
Audience
  • Developers
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Note
  • To request a customized training for this course, please contact us to arrange.
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Testimonials(25)

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

Alexandru - BRD
Course - Python Programming Fundamentals

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

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

very comprehensive in regards to doing data analysis using python

Mervin Lau - MINDEF
Course - Python for Data Analysis

Everything, great trainer.

Michał Rawicki
Course - Unit Testing with Python

Machine Translated

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

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

Michał
Course - Python for Excel

Machine Translated

examples and exercises

Kamil
Course - Introduction to Data Science and AI using Python

Machine Translated

Interesting knowledge

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

flexibility of approach to the client. the trainer was able to prepare issues that were of interest to the training participants.

Mirosław - CREDIT SUISSE (POLAND)
Course - Python Programming - 4 days

Machine Translated

Practical examples and wider context given.

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

I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.

Aurelia-Adriana - Allianz Services Romania
Course - Python and Spark for Big Data (PySpark)

examples based on our data

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

The fact that we were able to take with us most of the information/course/presentation/exercises done, so that we can look over them and perhaps redo what we didint understand first time or improve what we already did.

Raul Mihail Rat - Accenture Industrial SS
Course - Python, Spark, and Hadoop for Big Data

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)

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

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

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

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

Many different examples and topics has been covered, from basic investigation to login management and dynamic page management.

Daniele Tagliaferro - Creditsafe Italia Srl
Course - Web Scraping with 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

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

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

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

I genuinely enjoyed the lots of labs and practices.

Vivian Feng - Destination Canada
Course - Data Analysis with SQL, Python and Spotfire

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 did like the exercises.

Office for National Statistics
Course - Natural Language Processing with Python

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