Programming for Biologists

  28 hours

Python for Matlab Users

  14 hours

MongoDB for Python Developers

  14 hours

Python for Natural Language Generation

  21 hours

Natural Language Processing (NLP) with Python spaCy

  14 hours

PostgreSQL with Python

  21 hours

Advanced Python - 4 Days

  28 hours

Python: Automate the Boring Stuff

  14 hours

Analyzing Financial Data with Python

  35 hours

Web Scraping with Python

  7 hours

Python Programming Fundamentals

  14 hours

Advanced Python - 1 Day

  7 hours

Python with Plotly and Dash

  14 hours

Parallel Programming with Python

  14 hours

Automating with Python and SikuliX

  7 hours

Bioinformatics with Biopython

  14 hours

Python Fundamentals plus

  14 hours

Introduction to Data Science and AI using Python

  35 hours

Python Programming for Finance

  35 hours

Python in Data Science

  35 hours

Python for Excel

  14 hours

Python for Data Analysis

  28 hours

Data Analytics with Tableau, Python, R, and SQL

  35 hours

Machine Learning for Banking (with Python)

  21 hours

Machine Learning for Finance (with Python)

  21 hours

Applied AI from Scratch in Python

  28 hours

Recommender Systems with Python

  14 hours

Python: Machine Learning with Text

  21 hours

Text Summarization with Python

  14 hours

Machine Learning with Python – 2 Days

  14 hours

Machine Learning with Python – 4 Days

  28 hours

GANs and Variational Autoencoders in Python

  14 hours

Deep Learning for Banking (with Python)

  28 hours

Deep Learning for Finance (with Python)

  28 hours

Deep Reinforcement Learning with Python

  21 hours

Advanced Machine Learning with Python

  21 hours

Python, Spark, and Hadoop for Big Data

  21 hours

Natural Language Processing with Python

  28 hours

Natural Language Processing with Deep Dive in Python and NLTK

  35 hours

Building Chatbots in Python

  21 hours

Python Programming - 4 days

  28 hours

Backend Development with Python

  35 hours

BDD with Python and Behave

  7 hours

Test Automation with Selenium and Python

  14 hours

Unit Testing with Python

  21 hours

Learn Object-Oriented Programming with Python

  14 hours

Python and Spark for Big Data (PySpark)

  21 hours

Computer Vision with Python

  14 hours

Building Microservices with Python

  7 hours

Python for Geographic Information System (GIS)

  21 hours

Data Analysis with Tableau and Python

  14 hours

Data Visualization with Python

  14 hours

IoT Programming with Python

  14 hours

Deep Learning for Telecom (with Python)

  28 hours

Data Analysis with SQL, Python and Spotfire

  14 hours

Data Mining with Python

  14 hours

Python Security

  14 hours

Penetration Testing: Python and Kali Linux

  14 hours

Advanced Deep Learning with Keras and Python

  14 hours

ArcGIS with Python Scripting

  14 hours

Python for Network Engineers

  14 hours

Algorithmic Trading with Python and R

  14 hours

KNIME with Python and R for Machine Learning

  14 hours

Python and Deep Learning with OpenCV 4

  14 hours

Anomaly Detection with Python and R

  14 hours

Fraud Detection with Python and TensorFlow

  14 hours

Deploying Python Web Applications with Gunicorn

  7 hours

RabbitMQ with Python

  14 hours

GPU Programming with CUDA and Python

  14 hours

Apache Kafka for Python Programmers

  7 hours

Spark Streaming with Python and Kafka

  7 hours

ParlAI for Conversational AI

  14 hours

Continuous Integration / Continuous Delivery (CI/CD) with Python

  14 hours

GPU Data Science with NVIDIA RAPIDS

  14 hours

NLP with Python and TextBlob

  14 hours

Data Analysis with SQL, Python, and Tableau

  14 hours

I preferred the exercise and learning about the nooks and crannies of Python.

Connor Brierley-Green [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 [Python Programming]

Many examples made me easy to understand.

Lingmin Cao [Python Programming]

Fact that customization was taken seriously.

jurgen linsen [Python Programming]

I did like the exercises.

Office for National Statistics [Natural Language Processing with Python]

I liked the helpful and very kind.

Natalia Machrowicz [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 [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 [Python Programming]

I enjoyed the felixibility to add specific topics into the course / lessons.

Marc Ammann [Python Programming]

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

Sacha Nandlall [Python for Advanced Machine Learning]

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 [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 [Python Programming]

I genuinely enjoyed the lots of labs and practices.

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

The exercises/labs were tailored to our own organizational needs.

- Destination Canada [Data Analysis with SQL, Python and Spotfire]

I generally liked the subject matter.

- Destination Canada [Data Analysis with SQL, Python and Spotfire]

The trainer was sharing real word experiences, it's nice to learn from real professional.

- Fednot [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 [Advanced Python]

1:1 very intensive but learnt a lot.

Karen Dyke - BT [Python: Automate the Boring Stuff]

I mostly enjoyed the subject.

- Proximus [Python Programming]

The way the exercises were organized : all on own tempo and Antonio there to help you further.

- Proximus [Python Programming]

I liked the sufficient and very detailed reading materials and examples (slides).

- HC Consumer Finance Philippines, Inc. [Python Programming]

I genuinely liked the na.

- HC Consumer Finance Philippines, Inc. [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. [Python Programming]

The overview/the recommendations

frddy de meersman - Proximus [Python Programming]

Labs

- Proximus [Python Programming]

The informal exchanges we had during the lectures really helped me deepen my understanding of the subject

- Explore [Deep Reinforcement Learning with Python]

practice tasks

Pawel Kozikowski - GE Medical Systems Polska Sp. Zoo [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 [Python Programming]

It gave me a broad overview of the possibilites

- GE Medical Systems Polska Sp. Zoo [Python Programming]

really kind, good approach to trainees, helpful

- GE Medical Systems Polska Sp. Zoo [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 [Python Programming]

I thought John was very knowledgeable and able to diseminate information in a very understandable way.

- Crux Product Design [Python Programming Fundamentals]

John was a very friendly and knowledgeable trainer and was keen to adapt the course to our requests.

- Crux Product Design [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 [Python Programming Fundamentals]

knew his subject well

Albert JACOB - Proximus [Python Programming]

The exercises combined with the experienced help of the trainer

- Proximus [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 [Python Programming]

Trainer obviously had a great holistic understanding of programming.

- Crux Product Design [Python Programming Fundamentals]

the last day. generation part

- Accenture Inc [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 [Python for Natural Language Generation]

I enjoyed the sentinal analysis/ data science aspect of the course.

Jake Hamilton - Scottish Government [Python Programming]

pace and explanations

- Centric IT Solutions Lithuania [Advanced 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. [Python Programming Fundamentals]

Exercises

Vince Christian Henson - Cloudstaff Philippines, Inc. [Python Programming Fundamentals]

It makes the trick. A good introduction (and more) to python.

jean-christophe GOLDBERG - Proximus [Python Programming]

* Organization * Trainer's expertise with the subject

- ENGIE- 101 Arch Street [Python and Spark for Big Data (PySpark)]

Teaching style and ability of the trainer to overcome unforeseen obstacles and adopt to circumstances. Broad knowledge and experience of the trainer

ASML [Python for Matlab Users]

Overall good intro to Python. The format of using Jupyter notebook and live examples on the projector was good for following along with the exercises.

ASML [Python for Matlab Users]

Very good approach to memorize/repeat the key topics. Very nice “warm-up” exercises.

  [Python Programming]

I like that it focuses more on the how-to of the different text summarization methods

  [Text Summarization with Python]





Other regions in the UAE

Consulting

Python Consulting