LHL 0230 - Machine Learning
Overview
Discounted certificate pricing is available only to those who complete the certificate. If a student withdraws from the certificate program, they will be charged for the courses attended and assessed the full price of each course as follows: Data Wrangling $1,199.00; Machine Learning $1,999.00; Data Science $1,999.00.
Use machine learning to understand and enhance your analysis. Machine learning is the science which leverages data to get computers to make decisions without being explicitly programmed. We’ve all experienced the development of the self-driving car, speech recognition, face detection, and medical techniques to assist in diagnosing diseases. Today machine learning is being used to learn, classify, and predict in ways we could never imagine. This technology has become a part of everyday business throughout all industries.
In this course, you will learn about machine learning techniques, practice implementing them, and know when to use which machine learning models. You will explore the concepts of Feature Engineering and Dimensionality Reduction as it relates to data preparation, as well as learning about sampling, model selection, and differentiating between Machine Learning Models such as Unsupervised and Supervised Learning. The learning assessment is designed to apply the fundamental Machine Learning techniques and skills from the course to develop solutions in the context of a real-world problem.
Details for course:
- 40 hours; 10 sessions
- Tuesdays, Thursdays
- Classes will run from 6:00pm - 10:00pm
+ Features
Topics Covered:
- Data preparation
- Feature engineering
- Dimensionality Reduction
- Sampling
- Model Selection
- Machine Learning Models
- Supervised
- Classification
- Regression
- Decision Trees
- Neural Networks
- Unsupervised Learning
- Clustering
- Segmentation
- Anomaly Detection
- Time Series Analysis
- Supervised
Assessments:
- Project 1: Supervised Learning
- Project 2: Unsupervised Learning
+ Requirements
+ Designed For
This course is designed for individuals with web development experience wanting to obtain knowledge of Data preparation, Sampling, Model Selection, Machine Learning Models and Unsupervised Learning.
It is ideal for anyone wanting to advance their career in the tech industry or currently in roles that have more potential.
- Project/Security Manager
- System Administration
- Data Engineering
- Data Analyst
Expected Outcomes
- Explore how to extract value from the data to maximize the quality of the model.
- Apply Dimensionality Reduction techniques to reduce the dimension of the data with minimal loss of information.
- Explore the concept of Sampling in Machine Learning.
- Distinguish between different Machine Learning methods such as Model Selection.
- Explore the main differences between Supervised and Unsupervised Learning.
- Evaluate and apply fundamental Machine Learning methods to develop solutions for real-world problems.
- Apply correct Machine Learning algorithms to a defined problem.
- Identify a time dependent problem and implement the appropriate technique to solve the problem.
- Recall and implement the main steps (data preparation, feature engineering & dimensionality reduction, sampling, modeling and evaluation) that need to be followed during a data science project.
Applies Towards the Following Certificates
- Data Analytics Certificate : Required Courses