Developing AI and Machine Learning Solutions with Python Training
Developing AI and Machine Learning Solutions with Python Training
Training Developing AI and Machine Learning Solutions with Python - Online E-Learning Course. Order and start immediately for the best price.
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Developing AI and Machine Learning Solutions with Python E-Learning
Order this great E-Learning Training Developing AI and Machine Learning Solutions with Python online course!
✔️ 1 year 24/7 access to rich interactive videos, voice support, practice assignments, progress monitoring through reports and tests by topic to test your knowledge instantly.
✔️ After the course, you will receive a certificate of participation.
Why choose this course?
Artificial intelligence (AI) and machine learning (ML) are the fastest-growing technologies helping companies optimise their processes and make better decisions. Python is the most popular programming language for developing AI and ML solutions thanks to its simplicity, versatility and the power of the many libraries available. This course provides you with everything you need to develop AI and ML solutions with Python, from the basics of machine learning to implementing deep learning algorithms and robotic process automation (RPA).
What you will learn:
- Introduction to AI and Machine Learning: Understand the basic concepts of AI and ML, and how they are applied in different industries.
- Python for Machine Learning: Learn how to use Python to develop machine learning models, including popular libraries such as Scikit-learn, TensorFlow, and Keras.
- Deep Learning: Gain insight into deep learning algorithms and learn how to implement them to recognise complex patterns in data.
- Data preprocessing: Discover techniques for preparing data for machine learning models, such as data cleaning, feature selection and data augmentation.
- Robotic Process Automation (RPA): Learn how to use Python to develop RPA solutions to automate repetitive tasks in business processes.
- Evaluating and improving models: Understand how to evaluate and improve your ML models for better performance.
- Real-world applications: Study real-world examples and case studies of AI and ML applications in different industries, from healthcare to finance.
Who should participate?
This course is ideal for:
- Data scientists who want to expand their skills in Python and deepen their knowledge of machine learning.
- Software developers who want to integrate AI and ML functionality into their applications and systems.
- Engineers and researchers who want to learn how to use Python to develop AI and machine learning solutions.
- IT professionals who want to develop their career by learning how to apply AI and machine learning to their daily work.
- Students and beginners who are interested in artificial intelligence and machine learning and want to learn how to get started with Python.
- Business owners and entrepreneurs who want to use AI and machine learning to improve and automate business processes.
If you want to delve into developing AI and ML solutions and learn how Python plays an essential role in this process, then this course is perfect for you.
Course content
AI and ML Solutions with Python: Machine Learning and Data Analytics
Course: 1 Hour, 4 Minutes
- Machine Learning Concepts
- Machine Learning and Deep Learning Machine Learning and AI Correlation Installing Python for
- Machine Learning Analytics Types and Techniques Benefits of Predictive and Descriptive Analytics
- Nominal, Ordinal, Interval, and Ratio Data Metrics
- Supervised Learning Algorithm
- Implementing Regression
- Exercise: Working with Data Frames
AI and ML Solutions with Python: Supervised, Unsupervised and Deep Learning
Course: 1 Hour, 31 Minutes
- Working with Classification
- Unsupervised Learning
- K-Mean Clustering
- Hierarchical Clustering
- Text Mining and Recommender Systems
- Text Mining and Data Assemblz
- Deep and Reinforcement Learning Concepts
- Restricted Boltzmann
- Working with CNN
- Exercise: Working with Data Frames and Centroids
AI and ML Solutions with Python: Deep Learning and Neural Network Implementation
Course: 1 Hour, 3 Minutes
- Recurrent Neural Network
- Data Sampling
- Applying PCA
- Gaussian Regression Process
- Linear Model
- Pre-Model and Workflow
- Classification and Bayesian Ridge
- Linear Regression Modelling
- Logistic Regression Using Linear Method
- Exercise: Working with Linear Regression
AI and ML Solutions with Python: Implementing ML Algorithm Using scikit-learn
Course: 1 Hour, 14 Minutes
- Least Absolute Shrinkage
- Bayesian Ridge Regression Using scikit-learn
- Data Classification
- Decision Tree Classification
- Vector Machine Using scikit-learn
- Document Classification and Naive Bayes
- Post Model Validation
- Using Shufflesplit
- Brute Force Grid Search
- Exercise: Working with Decision Tree Classifiers
AI and ML Solutions with Python: Implementing Robotic Process Automation
Course: 1 Hour, 3 Minutes
- Fake Estimator
- Introducing Robotic Process Automation
- RPA Frameworks
- Implement Pattern Matching Using Python
- Task Scheduler and Program Auto Launch
- Manipulate Images
- File Operation Automation
- UiPath Fundamentals
- Implement RPA using UiPath
- Exercise: Working with Image Filters
Get started with AI and Machine Learning!
✔️ Flexible learning: Study the course at your own pace with rich interactive videos and voice support.
✔️ Hands-on learning: Apply your knowledge immediately through practical assignments and tests for each topic.
✔️ Certificate of participation: Receive a certificate of participation after successful completion of the course.
✔️ Boost your career: Learn how to develop AI and ML solutions that help companies make data-driven decisions.
Order your course now and become an expert in AI and machine learning with Python!
| Language | English |
|---|---|
| Qualifications of the Instructor | Certified |
| Course Format and Length | Teaching videos with subtitles, interactive elements and assignments and tests |
| Lesson duration | 5:55 Hours |
| Progress monitoring | Yes |
| Access to Material | 365 days |
| Technical Requirements | Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge. |
| Support or Assistance | Helpdesk and online knowledge base 24/7 |
| Certification | Certificate of participation in PDF format |
| Price and costs | Course price at no extra cost |
| Cancellation policy and money-back guarantee | We assess this on a case-by-case basis |
| Award Winning E-learning | Yes |
| Tip! | Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform. |
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