Introduction to Artificial Intelligence (AI) and Machine Learning (ML)
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About This Course
This introduction-level hands-on course explores the field of artificial intelligence (AI), programming, logic, search, machine learning (ML), and natural language understanding. You’ll learn current AI and ML methods, tools, techniques, and their application to computational problems.
In this course, we’ll cut through the math and you’ll learn exactly how machine learning algorithms work. We’ll focus on the algorithms used to create machine learning models. Using clear explanations, simple Python code (no libraries), and step-by-step labs, you’ll discover how to load and prepare data, evaluate your models, and implement a suite of linear and nonlinear algorithms along with assembling algorithms from scratch. You’ll also learn about algorithm applicability along with their limitations and practical use cases.
This course presents a wide variety of related technologies, concepts, and skills in a fast-paced, hands-on format. This provides you with a solid foundation for understanding and getting a jumpstart into working with artificial intelligence and machine learning.
Learning Objectives
Inclusions
- Instructor-led training
- Training Seminar Student Handbook
- Collaboration with classmates (not currently available for self-paced course)
- Real-world learning activities and scenarios
- Exam scheduling support*
- Enjoy job placement assistance for the first 12 months after course completion.
- This course is eligible for CCS Learning Academy’s Learn and Earn Program: get a tuition fee refund of up to 50% if you are placed in a job through CCS Global Tech’s Placement Division*
- Government and Private pricing available.*
Pre-requisites
- Basic Python skills
- A grounding in enterprise computing
- Be familiar with enterprise IT
- Have a general (high-level) understanding of systems architecture
- Knowledge of business drivers that might be able to take advantage of applying AI
- Good foundational mathematics in linear algebra and probability
- Basic Linux skills
- Familiarity with command line options such as ls, cd, cp, and su
Target Audience
- Business Analysts, Data Analysts, Developers, Administrators, Architects, Managers, and others new to AI and ML who want to understand the core skills and how to put them into practice.
Curriculum
1. Getting Started
Installing a Python Data Science Environment
Using and understanding iPython (Jupyter) Notebooks
Python basics: Part 1
Understanding Python code
Importing modules
Python basics: Part 2
Running Python scripts
2. Statistics and Probability Refresher and Python Practice
3. Matplotlib and Advanced Probability Concepts
4. Algorithm Overview
5. Predictive Models
6. Applied Machine Learning with Python
7. Recommender Systems
8. More Applied Machine Learning Techniques
9. Dealing with Data in the Real World
10. Apache Spark: Machine Learning on Big Data
11. Testing and Experimental Design
12. GUIs and REST
Your Instructors
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$1,795.00
Inclusions
- Instructor-led training
- Training Seminar Student Handbook
- Collaboration with classmates (not currently available for self-paced course)
- Real-world learning activities and scenarios
- Exam scheduling support*
- Enjoy job placement assistance for the first 12 months after course completion.
- This course is eligible for CCS Learning Academy’s Learn and Earn Program: get a tuition fee refund of up to 50% if you are placed in a job through CCS Global Tech’s Placement Division*
- Government and Private pricing available.*
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