Data Scientist Junior

Company: The AI Institute
Job type: Full-time

The AI Institute () trains its students in the US to
become operational Data Scientists in three months (480 hours of training).
The principle is as follows: we help you find a position as a Data Scientist
with one of our partner companies (often consulting firms) through our
extensive and well-rounded job search & placement services.
The hiring company finances the 3-months training course with us for an amount
of USD 10800. The hiring company (entity paying for your training) then
provides you with an employment letter for July, 2020. The training with The AI
Institute begins on April 1, 2020 for 3 months.
The objective of this training is to provide scientific graduates with the
tools, knowledge, and technical and human skills required or useful to become
a leader fully operational in Data Science and Artificial Intelligence
transformation and to know how to implement it in the business world, in
* Definition: Understanding Data Science; Artificial Intelligence; Machine
Learning and Deep Learning (neural networks): definitions and objectives;
discovering theoretical principles and foundations; discovering
programming tools (Python, Tensorflow).
* Tools: Master the main Data Science tools, statistical methods and their
applications in digital data processing and analysis; R; Python and
algorithm language workshops; SAS workshops; AWS workshops.
* Pass the Base Programmer SAS certification, the software most used by
* Pass the AWS Foundational certification to know how to deploy your
solutions on the cloud.
* Technical foundation: master the main techniques of Machine Learning,
Deep Learning and Neural Networks - understand how they work and know how
to implement them; data mining applications; practical workshops on Keras
and Tensorflow frameworks.
* Technologies: mastering AI technologies specific to image, video and
natural language processing, including convolutional neural networks,
particularly through Python and Tensorflow project workshops.
* Business cases: Know and understand the fields of application of AI in
companies through the analysis of many business cases of various
implementations (economic sectors, objectives, input data,
constraints...) to know where its use is possible, with which means,
risks and prospects of success.
* Project development: Know and understand how to build and carry out
innovation projects in AI; analyze pre-required data, generate innovative
ideas, take into account regulations, identify resources and expertise,
build an infrastructure, lead a prototype, manage iterations...
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