Requirements
- Python Programming Experience
- Basics of AI
- Basics of Linear Algebra, Calculus and Statistics
Target audiences
- Data Scientists
- Data Analysts
- Software Engineers
- AI Project Managers
Course Description
Master the core concepts of Machine Learning through in-depth, hands-on Python coding. This comprehensive course combines theoretical foundations with practical implementation of key ML algorithms. Designed for intensive learning, it offers a deep dive into both the principles and real-world applications of Machine Learning.
Start your journey as AI Engineer and Data Scientist, a most demanding field in computer science and artificial intelligence.
In today’s data-driven world, Machine Learning is a must-have skill for professionals in data science, software development, and business analytics. This course is ideal for those aiming to sharpen their analytical abilities and stay ahead in a competitive job market.
By the end of the course, delegates will be able to build prediction models and analyze data using Machine Learning algorithms.
What You’ll Learn From This Course
- Gain an in-depth understanding of the various algorithms of Machine Learning
- Understand different types of Machine Learning and how they work in Python
- Build data models and use them in algorithms
- Perform statistical analysis on data using Python
- Create and deploy prediction models
- Learn all Python libraries for ML
Curriculum
- 11 Sections
- 39 Lessons
- 3 Days
Expand all sectionsCollapse all sections
- Module 1: Machine Learning - Introduction4
- Module 2: Importance of Machine Learning2
- Module 3: Mathematics for Machine Learning2
- Module 4: Data Pre-Processing & Cleaning4
- Module 5: Supervised Machine Learning1
- Module 6: Classification Algorithms6
- Module 7: Regression Analysis7
- Module 8: Unsupervised Machine Learning2
- Module 9: Clustering6
- Module 10: Reinforcement Machine Learning2
- Module 11: Deep Learning3
Machine learning is a sub-field of AI that involves building models to make predictions based on data without being explicitly programmed.
The three types of machine learning are supervised learning, where models are trained on labelled data; unsupervised learning, which finds patterns in unlabeled data; and reinforcement learning, which learns from interaction with the environment and learns based on reward/penalty system.
Machine learning works by using algorithms to identify patterns in data. The model is trained on input training data, then models is tested for accuracy on test data and then makes predictions based on new data.
AI (Artificial Intelligence) is a broad term that refers to enable systems to acquire human intelligence, while ML (Machine Learning) is a subset of AI allowing systems to learn from data and improve over time.
The main objective of machine learning is to develop models to enable systems to learn from data, identify patterns, and make decisions without being explicitly programmed for each task.
An example of machine learning is recommending movies on Netflix, where algorithms are trained on a large dataset of users and their movie selections to automatically suggest movies for new viewers, based on patterns identified in the data.
Some drawbacks of ML include the need for high processing computers, large amounts of high-quality data, the risk of overfitting or underfitting models and potential biases in data leading to unfair outcomes.
Delegates must have a basic understanding of Python and Statistics.
Training includes hands-on live python coding sessions for algorithms and model development, concepts understanding with examples, study material (PDF) and training certificate from our UK partner institute.
This course takes 3-days to complete.
In this Machine Learning training, you will learn supervised, unsupervised and reinforcement learning, algorithm selection, data pre-processing and cleaning, model evaluation, and how to create machine learning models for real-world.
By the end of this Machine Learning course, you will learn data analysis, algorithm selection, model training and evaluation, feature engineering, creating and deploying machine learning models.
Basic understanding of Python programming, statistics, and mathematics will be beneficial.
After completing this training, you can start your journey towards Data Scientist, Machine Learning Engineer, AI Specialist, Data Analyst, or Research Scientist.
You can directly WhatsApp +44 7441 426446
Yes, the training includes hands-on activities, where you will work with real datasets, apply machine learning algorithms, and implement models using Python.
Oxford College of Technology and Management is a leading training provider for Machine Learning and AI, known for its updated course offerings and expert instructors. Our courses are interactive, allowing the delegates to have the same quality learning experience as a classroom session.
Oxford College of Technology and Management - UK is the Leading global training provider for Machine Learning and AI Courses.
Yes, delegates will be provided a certificate of completion from Oxford College of Technology and Management, London - UK.
Oxford College of Technology and Management is registered and approved by UK government at Companies House in England and Wales. Registration # 16434551 -
Oxford College is approved and recognized as an education provider by The UK Register of Learning Providers (UKRLP). UK Provider # 10098382
Oxford College is an approved education provider by European Union Education Commission. Approval # E10401966 -
Oxford College is an approved education vendor of European Commission. Approval # 871352941
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