Python Certification Training
Machine Learning with Python Training
Students who take Machine Learning with Python Training learn how to use Python to build, train, and test machine learning models. To solve real-world predictive analytics problems, you need to be able to use libraries like NumPy, Pandas, Matplotlib, and Scikit-learn.
5/5(4,890 Reviews)
Level
Advanced
Duration
8 weeks
What is Machine Learning with Python Training ?
This Machine Learning with Python Training gives you a solid understanding of machine learning ideas and how to use them. Participants will learn how to use supervised and unsupervised learning, how to evaluate models, how to engineer features, and how to optimize. The training includes hands-on coding for data preprocessing, regression, classification, clustering, and ensemble models. At the end of this program, students will be able to make ML models that can help businesses make decisions and learn more about their customers.
Training Plan
About trainer
Working professional who is carrying more then 10 years of industry experience.
Decks
The candidate will get access to the presentation taken-up during the session.
Notes
Consolidated notes in word document.
Assignments
Assignments for every module will be covered.
MCQs
MCQs for every module covered in the session would be provided.
Video Recording
Daily Session would be recorded and shared to the candidate.
Dumps for Certification
We will provide dumps for the certification exam, which will help you to prepare for the exam.
Updated Content
We provide Generative AI Driven content By experts.
Projects
3 Live Projects will be provided for practice.
Machine Learning with Python Training Course Curriculum
.
Introduction to Machine Learning & Python Basics
Section 1
Understand ML fundamentals and Python environment setup.
Machine learning overview
Python libraries for ML
Jupyter Notebook usage
Data loading & preprocessing
Key Projects
Machine Learning with Python Training
House Price Prediction
Use a housing dataset to make a regression model that can predict property prices based on things like location, size, and amenities. Use metrics like RMSE and feature engineering.
Spam Email Classifier
Use NLP preprocessing, TF-IDF vectorization, and algorithms like Naive Bayes and SVM to make a model that can tell the difference between spam and non-spam emails.
Customer Segmentation
Use clustering methods like K-Means and PCA on customer data to group users based on how they buy things. This will help businesses improve their marketing plans.
Machine Learning with Python Training – Associate Training Program
Category
Associate
Exam Name:
Machine Learning with Python Training – Associate
Exam Code:
N.A.
Exam Duration:
N.A.
Exam Format:
N.A.
Passing Score:
N.A.
Our Testimonials
Frequently Asked Questions (FAQs)
Is this training suitable for beginners in Machine Learning?
The course does start with the basics of Python and ML before moving on to more advanced topics. It is for people who are new to data, people who are interested in data, and people who want to learn more about machine learning.
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