CAIP-210 : Certified Artificial Intelligence (AI) Practitioner
Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services.
This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions.
The target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decision-making products that bring value to the business.
The duration of the program :
Classroom |
Live Online |
The skills covered in this course converge on four areas—software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems.
A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming.
- Lesson 1: Solving Business Problems Using AI and ML
- Lesson 2: Preparing Data
- Lesson 3: Training, Evaluating, and Tuning a Machine Learning Model
- Lesson 4: Building Linear Regression Models
- Lesson 5: Building Forecasting Models
- Lesson 6: Building Classification Models Using Logistic Regression and k-Nearest Neighbor
- Lesson 7: Building Clustering Models
- Lesson 8: Building Decision Trees and Random Forests
- Lesson 9: Building Support-Vector Machines
- Lesson 10: Building Artificial Neural Networks
- Lesson 11: Operationalizing Machine Learning Models
- Lesson 12: Maintaining Machine Learning Operations
This course is also designed to assist students in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification.
To ensure your success in this course, you should be familiar with the concepts that are foundational to data science, including:
• The overall data science and machine learning process from end to end: formulating the problem; collecting and preparing data; analyzing data; engineering and preprocessing data; training, tuning, and evaluating a model; and finalizing a model.
• Statistical concepts such as sampling, hypothesis testing, probability distribution, randomness, etc.
• Summary statistics such as mean, median, mode, interquartile range (IQR), standard deviation, skewness, etc.
• Graphs, plots, charts, and other methods of visual data analysis.
You can obtain this level of skills and knowledge by taking the CertNexus course Certified Data Science Practitioner (CDSP) (Exam DSP-110).
You must also be comfortable writing code in the Python programming language, including the use of fundamental Python data science libraries like NumPy and pandas. The Logical Operations course Using Data Science Tools in Python® teaches these skills.
| Location | Date | Time (UTC +2 ) | Delivery Format | Language |
|---|---|---|---|---|
| Live Online* |
20,21,22,23,24/11 | Mon-Fri 17:00-22:15 | Instructor Led | Greek/English |
* Σύγχρονη εξ αποστάσεως εκπαίδευση με εισηγητή – Virtual Class
Last update : 05/09/2023 (AI-102T00-A)
