6irdView 

San Jose Downtown 

99 South Almaden Blvd., Suite 600

San Jose, CA 95113

T: +1-408-579-9294

Email: contact@6irdview.com

©2019 by 6view

6irdView Presents 

Practical Machine Learning and iOS Bootcamp

8-Week Intensive Program with Two Distinguished Tracks 

Track 1: Applied Machine Learning

Track 2: iOS development

Training Plan

  • We equip students with the knowledge, skills, and industry-standard tools recommended to excel in applied machine learning and iOS app development. 
  • We guide students to apply those acquired skills to real-world applications through our project-based learning plan.
  • Based on students' performance, we may offer the opportunity to join 6irdview's team and build intelligent software

Program Overview

DESIGNED TO EQUIP SOFTWARE ENGINEERS AND PROGRAMMERS WITH SKILLS RECOMMENDED IN APPLIED MACHINE LEARNING AND GENERAL IOS DEVELOPMENT

Mission 

  • Our mission is to create a pipeline between Silicon Valley and Africa's emerging technology ecosystem. ​

  • We aim to bridge this gap by training a cohort of students at every iteration with the fundamental topics in iOS development, practical machine learning and data science.

APPLIED MACHINE LEARNING TRACK

More information

Please sign-up to request a detailed syllabus, course schedule, and/or enrollment information. 

Learning Objectives

Upon completion of training, students will be able to: 

  • Build end to end machine learning pipelines from data ingestion and exploration to a successful deployment of Machine Learning models.  

  •  Build and deploy statistical models, linear regression, data classification and visualization using cutting edge python frameworks and more

Prerequisites 

Prior to enrollment, we recommend students to be:

  • proficient in at least one programming language, preferably Python.

  • Familiar with basic computer science concepts, basic statistics, and linear algebra

Syllabus Overview

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Module 1

Week 1-2

  • Bootcamp Overview, Objectives & Outcomes

  • Python Overview

  • Introduction to Practical Machine Learning

  • Set Up of Development Environment & recommended tools and technologies 

  • End-to-end machine learning product demo
  • Reading and Video Assignments 

  • Hackathon 1

Module 2

Week 3-4

  • Machine learning use cases in industry

  • Selected supervised and unsupervised machine learning algorithms

  • Additional Reading and Video Assignments 

  • Hackathon 2

Module 3

Week 5-6

  • Data Engineering with SQL, pandas, numpy and command line tools

  • Selected supervised and unsupervised machine learning algorithms (continued)

  • Productization and Cloud part 1 

  • Preparation for final project/hackaton 

  • Module 2 recap 

  • Hackaton 3

Module 4

Week 7-8

  • Data Engineering with SQL, pandas, numpy and command line tools (continued)

  • Natural Language processing using spacy and FastAI 

  • Productization and Cloud part 2 

  • Advanced Topics and module 3 recap

  • Final capstone presentation 

Module 1

Week 1-2

  • Bootcamp Overview, Objectives & Outcomes

  • Python Overview

  • Introduction to Practical Machine Learning

  • Set Up of Development Environment & recommended tools and technologies 

  • End-to-end machine learning product demo
  • Reading and Video Assignments 

  • Hackathon 1

Module 2

Week 3-4

  • Machine learning use cases in industry

  • Selected supervised and unsupervised machine learning algorithms

  • Additional Reading and Video Assignments 

  • Hackathon 2

Module 3

Week 5-6

  • Data Engineering with SQL, pandas, numpy and command line tools

  • Selected supervised and unsupervised machine learning algorithms (continued)

  • Productization and Cloud part 1 

  • Preparation for final project/hackaton 

  • Module 2 recap 

  • Hackaton 3

Module 4

Week 7-8

  • Data Engineering with SQL, pandas, numpy and command line tools (continued)

  • Natural Language processing using spacy and FastAI 

  • Productization and Cloud part 2 

  • Advanced Topics and module 3 recap

  • Final capstone presentation 

iOS DEVELOPMENT

 TRACK

Learning Objectives

Upon completion of training, students will: 

  • Grasp Core Concepts of iOS App Development

  • Understand General User Interface (UI) Elements Programmatically

  • Learn Design Patterns using Model View Controller (MVC)

  • Learn how to connect iOS Apps to APIs,  and local storage

  • Build a Minimal Viable iOS App with common features such as feed, message listing etc.  

Prerequisites 

Prior to enrollment, we recommend students to be familiar with:

  •  C language & Object-Oriented Programming

  • Basic Networking Concepts, REST APIs

  • JSON

  • Firebase and AWS

To develop iOS apps using the latest technologies described in this track, you need a Mac computer (macOS 10.11.5 or later) running the latest version of Xcode.

More information

Please sign-up to request a detailed syllabus, course schedule, and/or enrollment information. 

Syllabus Overview

More information

Please sign-up to request a detailed syllabus, course schedule, and/or enrollment information. 

Syllabus Overview

I'm a paragraph. Click here to add your own text and edit me. It's easy.

Module 1

Week 1-2

  • Bootcamp Overview, Objectives & Outcomes

  • Introduction to iOS 11, Xcode, and Swift 4

  • MVC, iOS and Xcode Demonstration

  • Set- Up of Development Environment & recommended tools and technologies

  • Reading and Video Assignments 

  • Hackathon 1 - Part 1

Module 2

Week 3-4

  • Drawing in iOS

  • Multitouch gestures and Combining MVCs

  • Multiple MVCs

  • Animation

  • Additional Reading and Video Assignments 

  • Hackathon 2 - Part 2

Module 3

Week 5-6

  • View Controller Lifecycle and Scrolling 

  • Multithreading and Autolayout

  • Drag and Drop, Table View, Collection View, and Text Field

  • Preparation for final project/hackathon 

  • Module 2 recap 

  • Hackaton 3 - Part 3

Module 4

Week 7-8

  • Persistence & Documents

  • Alerts, Notifications, and Application Lifecycle

  • Segues

  • Core Motion & Camera

  • Accessibility

  • Final capstone presentation - Part 4

 
 

Meet Our Instructors

Elias

 

Hussen

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Elias is a world-class thought leader and expert in data analytics and engineering. He obtained his master's degree in Data Science, with a focus on Machine Learning, Statistics, and Data Engineering from Columbia University. 

During his studies, Elias researched and practiced concepts such as the Convolutional & Recurrent Neural Networks in Computer Vision and Natural Language Processing.

 

Moreover, his expertise expands to traditional machine learning algorithms such as linear/logistic regression, Principal Component Analysis, Support Vector Machines, decision trees, recommender systems, and ensemble methods. 

Elias held highly technical & reputable positions in the engineering and analytics departments of the most influential finance, media and technology companies such as Vice Media, Bank of America, Unified Social, and On Deck Capital. 

Throughout his career, Elias has architected big data pipelines, massive data warehouses, complex machine learning models and python-based cloud applications. 

In his last recent role as a senior data and machine learning engineer at Vice Media, Elias has built, along with a team of engineers and analysts, intelligent applications that use the latest deep learning algorithms to accurately predict sentiment and topics of a corpus of text.

Dagmawi

 

Assefa

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Dagmawi is a serial entrepreneur and software engineer specializing in iOS mobile app development and artificial intelligence. 

 

Dagmawi obtained his bachelor’s degree in Information Communication Technology with a minor in Computer Science from the University of Kentucky.  

Dag has extensive experience using tools such as Xcode, AWS Lambda, Firebase, CoreData, and Sketch.

 

He is also well versed in programming languages such as Swift, Python, C++, C, Javascript,  Kotlin, Dart, Flutter, Net, MySQL, JQuery, PHP, AngularJS, ASP.NET.  
 

He has successfully launched Sason, a smart photo editor app in the App Store that has reached Top 500 Apps List in 7 countries. Sason has a unique feature that suggests how to compose a picture and how to frame the subject in the picture. 

Currently, he is working on launching a similar product, Capture, an iOS smart camera powered by Artificial Intelligence. An app that allows users to analyze and score the visual quality in real-time.

Dagmawi and his team trained their machine learning model using aws-cli and developed algorithms that process lookup tables to enhance images.

 

INFO REQUEST

To request additional information on our training program, please take the time to fill out the information below.

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Gobeze Training Center

We have arranged a place for you to learn in a hands-on and interactive from our world-class instructors.

Location: Bole sub-city, woreda 03

Zewdu Gessesse Building (Ice Addis is located here)

House No. 2414 - 2nd floor 

Addis Ababa, Ethiopia

Behind Bole Medhanealem Church, towards Moenco 

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