Rigorous On-Site Bootcamp During Weekends

Offered in New York, Boston and Washington DC

USD 8,000.00
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Instructor
, Instructor - Deep Learning with TensorFlow Weekends

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Instructor:

Deep Learning Weekend Bootcamp 8 weeks

Course Description

The weekend bootcamp lasts 8 weeks and covers the most important aspects of Machine Learning/Deep Learning. The course consists of theory, coding and labs that will introduce you to the bleeding edge of Data Science and Deep Learning.

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What am I going to get from this course?

You will be able to apply Deep Learning techniques, primarily TensorFlow to solve real-world business problems and extract insights and value from business data sets. This course will prepare candidates for a transition into a Data Science role. 

Prerequisites and Target Audience

What will students need to know or do before starting this course?

Students should know basic python programming, elementary statistics, basic calculus and linear algebra. Any business experience is a bonus. Background in physical sciences, computer sciences, or mathematics is ideal. 

Who should take this course? Who should not?

Candidates should take this course if they have a good grounding in the physical sciences or business experience as a software engineer and are comfortable in statistics and/or mathematics. Candidates without a strong mathematics and programming background will need to spend extra time covering the fundamentals or taking preliminary programming and statistics courses. 

Curriculum

Module 1: Week 1

Lecture 1 Data Science Overview

Background and Market, Cloud computing platforms, Statistical analysis as applied to Data Science, Deep Learning Frameworks

Module 2: Week 2

Lecture 2 Hadoop, Spark and Flink

Hadoop Overview - Yarn, Ambari, MapReduce, Spark Release 2.0, Introduction to, Flink, Labs

Module 3: Week 3

Lecture 3 Python and Julia

Python Programming Overview, Python libraries including SciPy, NumPy, and, Matplotlib, Scikit-Learn, Introduction to Julia Programming, Labs

Module 4: Week 4

Lecture 4 Machine Learning

Overview of Machine Learning Frameworks , Supervised learning, Unsupervised learning, Reinforcement learning, Labs

Module 5: Week 5

Lecture 5 Deep Learning I

Overview of Computer Vision, Convolutional Neural Networks with applications, GPU computing and technology, TensorFlow Labs

Module 6: Week 6

Lecture 6 Deep Learning II

Introduction to Natural Language Processing, Overview of Recurrent Neural Networks, LSTM with applications, TensorFlow Labs

Module 7: Week 7

Lecture 7 Deep Learning III

Deep reinforcement learning, Introduction to Gaussian processes, Cognitive computing overview, TensorFlow Labs

Module 8: Week 8

Lecture 8 IoT, Visualisation & Reporting

Overview and applications of IoT, Visualization tools including d3 and Shiny, Business Reporting, Wrap up