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Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503)

4.6 out of 5 rating Last updated 14/11/2024   English

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Duration

3 Days

18 CPD hours

Overview

Working in a hands-on learnng environment led by our expert practitioner you'll explore:
-Grasp AI & Machine Learning Basics: You'll start your journey by understanding what AI and Machine Learning are, distinguishing between them, and discovering how they're applied in various fields. You'll also get a good look at practical examples of Machine Learning.
-Decode Types of Machine Learning: You'll navigate through the different types of machine learning, including supervised, unsupervised, and reinforcement learning, and gain insight into their distinctive applications, and explore their practical application.
-Master Data Prep: You'll learn and apply critical methods for cleaning and simplifying data
Master Algorithms: You'll explore popular machine learning algorithms, their applicability and limitations
-Get Hands-On: You'll learn how to code linear regression and logistic regression algorithms in Python, and gain hands-on experience applying them in real-world scenarios in a machine learning environment working with various machine learning packages and tools.
-Optimize Machine Learning Models: You'll dig into the art of model optimization, learning how to prevent underfitting and overfitting to ensure your machine learning models are accurate and reliable.
-Conquer Classification: You'll uncover the secrets of the perceptron algorithm and logistic classifiers, learning how to classify data effectively and carry out sentiment analysis like a pro.
-Responsible AI Development: You'll gain insight into the ethical considerations and responsible practices in AI, ensuring that solutions are developed with a consciousness of privacy, bias, and societal implications.
-Venture into Generative AI: You'll step into the fascinating world of Generative AI and Generative Adversarial Networks (GANs), exploring their structure, functionality, and the concept of latent space in generative models. After the course, you'll understand how these advanced AI models can contribute to your projects.

Description

Geared for technical professionals, our Introduction to AI & Machine Learning JumpStart course is a three-day, hands-on workshop style event designed to get you quickly up and running with latest skills, tools and tech in essential AI and ML, demystifying the field of artificial intelligence without drowning you in mathematics. Whether you're a budding developer or a tech enthusiast, we'll guide you through the foundations of AI and machine learning, and equip you with the knowledge, problem-solving skills and confidence needed to apply this innovative tech in real-world scenarios.
The course is rich with hands-on activities, challenge labs, knowledge checks, valuable discussions and focused projects that can be done individually or in groups. Working in a hands-on learning environment, guided by our engaging AI expert, you'll explore AI and Machine Learning essentials, practical examples, tools and best practices. You'll learn how to integrate AI and machine learning principles into real-world projects, enabling you to innovate in areas like product development, customer experience enhancement, and complex problem-solving. You'll explore the differences and applications of supervised, unsupervised, and reinforcement learning, laying the groundwork for exploration and utilization in diverse contexts. You'll learn how to employ AI and machine learning concepts for making informed, data-driven decisions that can have far-reaching impacts on various aspects of business and technology.
Throughout the course you'll gain highly-valuable, expert guided experience using cutting-edge tools and algorithms through hands-on labs, ensuring that you can confidently apply these new skills and concepts in practical scenarios. You'll leave the event well-versed and ready to apply key AI and Machine Learning concepts in your work. Whether you'll be coding algorithms, classifying data, or optimizing machine learning models, you'll have the essentials skills needed to tackle any AI-related project.

Prerequisites

Pre-Requisites: Students should have attended or have incoming skills equivalent to those in this course:
-Basic Understanding of Python as well as familiarity with Python Libraries (Pandas and Numpy, etc.). Attendees without Python background may view labs as follow along exercises or team with others to complete them.
-Basic Linux skills, including familiarity with command-line options such as ls, cd, cp, and su
-Basic Math and Problem-Solving Skills
-Understanding of Basic Data Structures

1. What is AI and Machine Learning
¢ Is machine learning difficult
¢ What is artificial intelligence
¢ Difference between AI and machine learning
¢ Machine learning examples

2. Types of Machine Learning
¢ Three different types of machine learning: supervised, unsupervised, and reinforcement learning
¢ Difference between labeled and unlabeled data
¢ The difference between regression and classification, and how they are used

3. Linear Regression
¢ Fitting a line through a set of data points
¢ Coding the linear regression algorithm in Python
¢ Using Turi Create to build a linear regression model to predict housing prices in a real dataset
¢ What is polynomial regression
¢ Fitting a more complex curve to nonlinear data
¢ Examples of linear regression

4. Optimizing the Training Process
¢ What is underfitting and overfitting
¢ Solutions for avoiding overfitting
¢ Testing the model complexity graph, and regularization
¢ Calculating the complexity of the model
¢ Picking the best model in terms of performance and complexity

5. The perceptron Algorithm
¢ What is classification
¢ Sentiment analysis
¢ How to draw a line that separates points of two colors
¢ What is a perceptron
¢ Coding the perceptron algorithm in Python and Turi Create

6. Logistic Classifiers
¢ Hard assignments and Soft assignments
¢ The sigmoid function
¢ Discrete perceptrons vs. Continuous perceptrons
¢ Logistic regression algorithm for classifying data
¢ Coding the logistic regression algorithm in Python

7. Measuring Classification Models
¢ Types of errors a model can make
¢ The confusion matrix
¢ what are accuracy, recall, precision, F-score, sensitivity, and specificity
¢ what is the ROC curve

8. The Naive Bayes Model
¢ What is Bayes theorem
¢ Dependent and independent events
¢ The prior and posterior probabilities
¢ Calculating conditional probabilities
¢ using the naive Bayes model
¢ Coding the naive Bayes algorithm in Python

9. Decision Trees
¢ What is a decision tree
¢ Using decision trees for classification and regression
¢ Building an app-recommendation system using users' information
¢ Accuracy, Gini index, and entropy
¢ Using Scikit-Learn to train a decision tree

10. Neural Networks
¢ What is a neural network
¢ Architecture of a neural network: nodes, layers, depth, and activation functions
¢ Training neural networks
¢ Potential problems in training neural networks
¢ Techniques to improve neural network training
¢ Using neural networks as regression models

11. Responsible AI: Navigating the Grey Areas
¢ Understanding Ethical Implications in AI
¢ Grasp the moral complexities in recommendation systems.
¢ Bias and Fairness in Recommenders
¢ Dissect potential biases in AI-driven recommendations.

12. Introduction to Generative AI
¢ Understanding Generative AI
¢ How Generative AI fits into the broader AI and Machine Learning landscape
¢ Differences between generative and discriminative models
¢ Introduction to Generative Adversarial Networks (GANs)
¢ Understanding the concept of latent space in generative models
¢ Basic structure and components of GANs: generator and discriminator

13. OPTIONAL: Applications of Generative AI in Business
¢ Improving customer experience: Using generative AI for personalized content creation, such as emails, ads, and product descriptions
¢ Product development: Using GANs for generating new ideas for products, fashion designs, and more
¢ Data augmentation: How generative models can create additional training data for other machine learning models, improving their performance
¢ Content creation: Using AI for generating realistic images, music, text, and more
¢ Risk management: Using generative AI to simulate different business scenarios and outcomes
¢ Healthcare: Generating synthetic medical data for research while preserving patient privacy

Bonus Content / Time Permitting

14. Bonus: Support vector machine and the Kernel methods
¢ What a support vector machine
¢ Which of the linear classifiers for a dataset has the best boundary
¢ Using the kernel method to build nonlinear classifiers
¢ Coding support vector machines and the kernel method in Scikit-Learn

15. Bonus: Ensemble learning
¢ What ensemble learning is
¢ Using bagging to combine classifiers
¢ Using boosting to combine classifiers
¢ Ensemble methods: random forests, AdaBoost, gradient boosting, and XGBoost

16. Bonus: Real-World Example: Data Engineering and ML
¢ Cleaning up and preprocessing data to make it readable by our model
¢ Using Scikit-Learn to train and evaluate several models
¢ Using grid search to select good hyperparameters for our model
¢ Using k-fold cross-validation to be able to use our data for training and validation simultaneously
Additional course details:

Nexus Humans Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.

This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts.

Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.

While we feel this is the best course for the ITS Data Analytics course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.

Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

FAQ for the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) Course

Available Delivery Options for the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training.
  • Live Instructor Led Classroom Online (Live Online)
  • Traditional Instructor Led Classroom (TILT/ILT)
  • Delivery at your offices in London or anywhere in the UK
  • Private dedicated course as works for your staff.
How many CPD hours does the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training provide?

The 3 day. Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training course give you up to 18 CPD hours/structured learning hours. If you need a letter or certificate in a particular format for your association, organisation or professional body please just ask.

Which exam does the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training course prepare you for?

The Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) prepares you for the Yes official exam. You can take this exam at any exam center across UK including, England, Scotland, Cymru (Wales) or Northern Ireland or live online where ever you are. Exams vary in duration and if required you can request with the provider for any accommodations appropriate for you.

What is the correct audience for the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training?

This introductory-level hands-on course is suited for a wide variety of technical learners who need an introduction to the core skills, concepts, tech, tools and skills related to AI programming and machine learning.
Suitable attendees might include:
-Developers aspiring to be a 'Data Scientist' or Machine Learning engineers
-Analytics Managers who are leading a team of analysts
-Business Analysts who want to understand data science techniques
-Information Architects who want to gain expertise in Machine Learning algorithms
-Analytics professionals who want to work in machine learning or artificial intelligence
-Graduates looking to build a career in Data Science and machine learning

Do you provide training for the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503).

Yes we provide corporate training, dedicated training and closed classes for the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503). This can take place anywhere in UK including, England, Scotland, Cymru (Wales) or Northern Ireland or live online allowing you to have your teams from across UK or further afield to attend a single training event saving travel and delivery expenses.

What is the duration of the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) program.

The Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training takes place over 3 day(s), with each day lasting approximately 8 hours including small and lunch breaks to ensure that the delegates get the most out of the day.

What other terms do people search for when looking for this course?

Popular related searched include AI; Machine Learning.

Why are Nexus Human the best provider for the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503)?
Nexus Human are recognised as one of the best training companies as they and their trainers have won and hold many awards and titles including having previously won the Small Firms Best Trainer award, national training partner of the year for UK on multiple occasions, having trainers in the global top 30 instructor awards in 2012, 2019 and 2021. Nexus Human has also been nominated for the Tech Excellence awards multiple times. Learning Performance institute (LPI) external training provider sponsor 2024.
Is there a discount code for the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training.

Yes, the discount code PENPAL5 is currently available for the Introduction to AI, AI Programming & Machine Learning | AI / ML JumpStart (TTML5503) training. Other discount codes may also be available but only one discount code or special offer can be used for each booking. This discount code is available for companies and individuals.

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Training Insurance Included!

When you organise training, we understand that there is a risk that some people may fall ill, become unavailable. To mitigate the risk we include training insurance for each delegate enrolled on our public schedule, they are welcome to sit on the same Public class within 6 months at no charge, if the case arises.

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