Career Training Programs

Machine Learning Course

Prerequisites for the course: Working knowledge of Python programming, undergraduate mathematics, and CLI experience.

Emphasis will be on hands on development, going through exercises and workshops together. Very little reading.

Cost of the Course: $5,000

  1. Machine Learning Overview
    1. Introduction
    2. Uses for Machine Learning
    3. Environment configuration for Python Development with Anaconda IDE
    4. Python Library Imports
  2. Preprocessing
    1. Importance of data management
    2. Difference Between Independent and Dependent Variables in Data Science
    3. How to Import Data and Segment I and D Variables
    4. Script development for cleaning data
      1. Object Inspection
      2. Replacing NaN Cells in Python with the Mean, Median and Mode
    5. Missing value management
    6. Setting up a Test and Training Set of Data
    7. Normalization and Feature Scaling
    8. Data categorization
    9. Numpy
      1. Arrays
        1. Dtype
        2. Upcasting: Implicit Casting, Astype, Structured Array
        3. Copy function
        4. Nan for placeholder element
        5. Inf for infinity
        6. transposing
  3. Regression
    1. Linear regression
      1. 5 Assumptions of a Linear Regression
      2. Simple
      3. Multiple
      4. Polynomial
    2. Decision Trees
    3. Forests
  4. Classification
    1. Naive bayes
      1. Generative vs Discriminative Models
      2. Spam classification system
    2. K Nearest Neighbors
      1. Visualizations
      2. XOR Problem
    3. Decision Trees
      1. Information Entropy
      2. Maximizing Information Gain
    4. Random forest
    5. Logistic regressions
    6. Perceptron Concepts
    7. Bias-Variance
    8. Adaboost
  5. Bayesian Networks
    1. Overview
    2. Probability Management
    3. Exploring and Exploiting
    4. Threshold Management
    5. Building an A/B Testing system
    6. Multivariate Gaussian Likelihood
  6. Clustering
    1. K Means Clustering
    2. Hierarchy based clustering
    3. Cluster visualizations
  7. Neural Networks
    1. Overview
    2. Tensorflow
    3. Image recognition
    4. Boltzmann Machines
    5. Intuition Development
    6. Convolutional vs Artificial vs Recurrent
    7. LeNet
    8. Theano
    9. Facial Recognition Engine
    10. Convolutional Neural Networks (CNN)
    11. Artificial Neural Networks (ANN)
    12. Recurrent Neural Networks (RNN)
  8. Vendor Machine Learning Systems
    1. Google NLP engine
    2. AWS NLU (Natural Language Understanding)
    3. AWS Predictive Models
  9. Special Machine Learning Problem Case Studies
    1. Markov Decision Processes
    2. Rebuilding Google PageRank
    3. Monte Carlo
    4. Temporal Difference Learning
    5. Approximation Methods

The Career Training Division – Bottega is NOT accredited by DEAC and is not eligible for VA funding.

Mobile Development with React Native Certificate Programs

https://bottega.edu/mobiledevelopment/

 

The student will learn to build a functional mobile app from scratch that runs on Android and IOS. A mobile app that is dynamic, full of modern features, and connected to an API provided by Bottega.

 

The Career Training Division – Bottega is NOT accredited by DEAC and is not eligible for VA funding.

[ ] No Prerequisites • Full-Time Online • Tuition 4,500 USD

Estimated at 220 hours (6** weeks Full-Time).

[ ] No Prerequisites • Part-Time Online • Tuition 3,500 USD

Estimated at 220 hours (15* weeks Part-Time)

[ ] For Developers • Part-Time • Tuition 2,500 USD

Estimated at 160 hours (11* weeks Part-Time).

[ ] For React Developers • Part-Time • Tuition 1,500 USD

Estimated at 105 hours (7* weeks Part-Time)

 

 * Part time schedule estimated time to completion based on a required minimum 15 hours per week for online study, test and quiz prep, time allotted to take tests and quizzes, course work, homework and time to build capstone. If a student dedicates more than 15 hours per week, completion time will be shorter.

**Time zone will vary. For a full-time remote student, be aware that all classes are in the Mountain Time Zone.

***************************  PART-TIME   ***************************

[ ] Front End Development – Vue.js + React.js

Tuition $7,500 USD 

The Vue.js + React.js curriculum. The student will learn the foundation level of the main programming languages and completes industry equivalent entry-level software programming projects. Estimated at 600 hours (10 months, 40 weeks Part-Time)

 

Computer

MacBook Pro or a PC within 4 years of Age, 2.0GHZ-2.3GHZ, i5 or i7, 8-16 gb of RAM – 500 gb-1 TB  harddrive

Webcam

Resolution at least 640 x 480 with 1280×720 recommended.

Microphone

Many webcams have built in microphones.

Speaker

Or headphones connected to the computer.

Chrome Web Browser

Most current version with Adobe Flash Player installed. Adobe Flash Player is a free download from adobe.com.

Internet

Reliable high-speed Internet connection of at least 10-15 Mbps.

Microsoft Office

Adobe PDF Reader