Artificial Intelligence and Machine Learning Bootcamp

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Machine Learning and Artificial Intelligence Foundations Bootcamp

Hybrid Format: Asynchronous online learning with face-to-face labs

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Starting May 5, 2019

Introduction

Machine learning is a particular approach to artificial intelligence. And Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed.

Artificial intelligence is the simulation of human intelligence through machines using computer systems. Artificial Intelligence is an enormous field. It comprises of various disciplines and a variation of tools and platforms. There is no boundary to what these artificial intelligence techniques can be applied across numerous business domains.

‘By the 2030s around 38% of all U.S. jobs could be replaced by AI and automation.’ – PWC

The good news is that online courses make it possible for practically anyone to become an expert on the subject. The Allegro AI/ML Bootcamp is an effective way to jumpstart a move to the Artificial Intelligence field.

Program Goals

  • To build job ready skills with focus on key areas such as advanced machine learning, natural language processing, or deep learning.

 

  • To develop a professional portfolio – 10 real-life projects, including two industry-worthy capstone projects to showcase your skills to employers.

 

  • To learn the best practices through 1:1 mentorship – personalized career coaching and 1:1 mentorship from industry experts.

Program Coverage

Week 1

Overview of AI and Machine Learning Engineering Stack

  • Learn about the different branches of AI, and the difference between AI, Machine Learning and Data Science.
  • Get introduced to the tools and libraries used in the worlds of data science and engineering.
  • Learn software engineering best practices that apply to AI/ML practitioners.

Week 2

Data Wrangling at Scale and Statistics for AI

  • Collect data at scale from APIs, real-time systems, and websites.
  • Transform this data efficiently and effectively so that ML algorithms can crunch it down the pipeline.
  • Use frequentist statistical inference and hypothesis testing to draw insights from data.

Week 3

Foundations of Machine Learning

  • Explore the most important supervised and unsupervised machine learning algorithms.
  • Learn when and how to implement these algorithms at scale.

Week 4

A Deep Dive into Deep Learning

  • Establish a thorough foundation in deep learning and build real-world applications.
  • Learn about neural network principles and engineering frameworks such as Keras and PyTorch.

Week 5

AI Case Study 1: Natural Language Processing

  • Learn the basics of text data, including how to clean and process it, and how to extract insights from text and conversations.
  • Work through a detailed case study and solve a real NLP problem using deep learning and other techniques.

Week 6

AI Case Study 2: Computer Vision

 

  • Learn image processing techniques and solve a real image processing problem.
  • Dive into the foundations of computer vision and deep learning for images.

Week 7

Building and Deploying Large-Scale AI Systems

  • Apply what you’ve learned in this course by developing a realistic, large-scale, deployed AI system.
  • Learn about common tools and techniques, deploying ML applications, real-time data processing, and making your application available via API or a web service.

Week 8

Capstone Project

  • Build a realistic, complete, large-scale API application that’s available to use via an API, a web service, or — optionally — a website.
  • You’ll have free access to a cloud-based engineering environment, which will support all of the standard tools and libraries.

Week 9

Career Support

  • Get personalized guidance from our career coaches to find your dream MLE job.
  • This support includes resume feedback, mock interviews, negotiation strategies, and more

Blended Hybrid Model as well as fully online program delivery option

Rather than passively receiving and reiterating information, you can take an active role in your education and contribute to your own learning. You can work with the faculty members to set learning goals for yourself, and can work toward them through blended learning by combining face-to-face interaction with your faculty through an asynchronous online learning with bi-weekly face-to-face labs.

But if you have choose the fully online model for whatever reason, you can choose to complete the program online without needing to join the face-to-face sessions at the campus.

Eligibility Criteria

Bachelor’s/Master’s degrees in Computer Science/Engineering/Math/Statistics/ Economics/Science

Attend an Information Session

Register to attend an upcoming information session

Contact a Program Counselor @ 717-674-4532 for more information.

How do you join?

 

There are limited seats for this batch and selection is based on review of your application and a telephone interview.

Apply

Wait for Selection

Pay Semester Fee

Register for Courses

Batch Start


Seats are limited

Register to receive notice of the release of the online application.

About Allegro Learning Solutions

Accredited by the Middle States Commission on Higher Education, Harrisburg University is known for their outstanding science and technology-focused degree programs. The institution fosters a diverse community of learners, provides access and support to students who want to pursue a career in science and technology and supports business creation and economic development.

https://www.allegrolearnings.com

About ACubeIT

ACubeIT is an AI teaching, research & consulting company that offers programs to individual students, colleges and corporate through intensive custom training and workshops. ACubeIT delivers programs in product development, AI driven financial risk management system, AI consulting and AI practice development for consulting companies.  Core team members at ACubeIT have have been teaching Machine Learning courses at leading business schools and corporates.

http://www.acubeit.com