Machine-Learning IN chennai

Computers' ability to learn and make decisions without explicit programming is being revolutionised by machine learning, a branch of artificial intelligence. Machine learning is at the core of this change, allowing computers to evaluate data, spot patterns, and improve performance over time. These algorithms are able to adjust to a wide range of settings by continuously improving their understanding via experience, whether it be through speech recognition, personalised content recommendations, or trend prediction. This game-changing technology is now widely used, influencing industries like healthcare, banking, and entertainment while spurring innovation and forming a future centered around data.

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Instructional Format Online
Live Courses 3 Months
Executive Course Certification
45+ Hiring Partners
Mentorship Support Placement Support
Resume Building Assisting mock

Machine-Learning Course Overview

A Machine Learning course provides a comprehensive exploration of the principles, algorithms, and applications that drive the field of machine learning. The curriculum is designed to equip participants with the knowledge and practical skills necessary to understand, implement, and deploy machine learning models

Key-Highlights
  • 60+ hours of live classroom training
  • Projects aligned in domains industries
  • Master more than ten stack tools.
  • 2 live Projects
  • 24*7 Support
  • Certification
  • Individual Consultation Industry Experts
  • Placement Support
  • Mock Job Interviews
  • Zero-Interest EMI
  • Flexible Session Scheduling
  • Discussion through Class

Machine Learning Certification

A course on machine learning provides a thorough analysis of the underlying theories, computational techniques, and practical applications. The course material is designed to give learners the fundamental understanding and useful abilities required to efficiently understand, apply, and use machine learning models.

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Testimonials

GokulRaj

Machine-Learning

"The Machine Learning certification program was informative, but I felt that certain topics could have been covered in more detail. Additionally, more emphasis on real-world applications and case studies would have been beneficial. Despite this, the program provided a solid foundation, and the support from the community was valuable."

Aravindh

Machine-Learning

"Completing the Machine Learning certification program was a game-changer for my career. The well-structured curriculum covered a broad range of topics, and the hands-on projects provided practical experience. The instructors were knowledgeable and responsive, and the certification has significantly enhanced my confidence and competence in the field."

Who Is Eligible to Apply for the Course?
  • Working professionals in the IT industry seeking to transition into AI development or upgrade their skills may be eligible.
  • Students currently enrolled in computer science or related degree programs who wish to enhance their skills may be eligible.
  • Perfect for beginners!"
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Machine Learning-Syllabus

Module 1: Introduction to Machine Learning
  • Definition and types of machine learning: supervised, unsupervised, reinforcement
  • Overview of applications and case studies
  • Ethical considerations in machine learning
Module 2: Data Preprocessing and Exploration
  • Data cleaning and handling missing values
  • Exploratory Data Analysis (EDA)
  • Feature scaling and normalization
  • Feature engineering and selection
Module 3: Supervised Learning
  • Linear regression and logistic regression
  • Decision trees and ensemble methods (Random Forests)
  • Support Vector Machines (SVM)
  • k-Nearest Neighbors (k-NN)
  • Evaluation metrics for classification and regression
Module 4: Unsupervised Learning
  • Clustering techniques: K-Means, Hierarchical, DBSCAN
  • Dimensionality reduction: Principal Component Analysis (PCA)
  • Anomaly detection
  • Association rule learning
Module 5: Neural Networks and Deep Learning
  • Introduction to neural networks
  • Feedforward neural networks and backpropagation
  • Convolutional Neural Networks (CNN) for image data
  • Recurrent Neural Networks (RNN) for sequential data
Module 6: Model Evaluation and Hyperparameter Tuning
  • Cross-validation techniques
  • Hyperparameter tuning and grid search
  • Model evaluation metrics and confusion matrices
Module 7: Natural Language Processing (NLP)
  • Text preprocessing and tokenization
  • Word embeddings (Word2Vec, GloVe)
  • Sentiment analysis
Module 8: Reinforcement Learning
  • Basics of reinforcement learning
  • Markov Decision Processes (MDP)
  • Q-learning and policy gradient methods
Module 9: Model Deployment and Scaling
  • Deployment strategies for machine learning models
  • Introduction to cloud services for model deployment
  • Scalability considerations and best practices
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Job Search Pre-interview Planning Resume Building
Guaranteed Interviews

Interviews guaranteed upon project and assignment submission. Interview with more than 45+of our hiring partners.


special access to the Jobs portal on Inetz

Dedicated job portal access with exclusive job applications. Over 45+ hiring partners, such as leading product companies and start-ups, are employing our learners. coached assistance in finding suitable jobs to advance your career.

Prepare for Mock Interviews

Technical experts will conduct several mock interviews with students, after which they will provide advice and helpful for future reference.


Individualized Career Guidance Sessions

Attend one-on-one meetings with career mentors to discuss how to cultivate the necessary abilities and mindset to land a dream job based on the educational background, prior work experience, and future career goals of learners.

Sessions with a Career Focus

Participate in more than 15 live, interactive sessions with an industry expert to learn and gain experience developing the kind of skills hiring managers look for. You will be able to stay on track with your upskilling goal by attending these guided sessions.


Building a LinkedIn Profile and Resume

Our career services team can help you create a stellar resume and LinkedIn profile. You can also learn how to attract the hiring manager's attention during the profile shortlisting stage.

Frequently Asked Questions

What job opportunities are available in Machine Learning?

Machine Learning professionals can pursue roles such as Machine Learning Engineer, Data Scientist, AI Research Scientist, Computer Vision Engineer, Natural Language Processing (NLP) Engineer, and more. Industries such as technology, finance, healthcare, and e-commerce actively hire machine learning experts.

Do I need a specific degree for a career in Machine Learning?

While a background in computer science, mathematics, or a related field is beneficial, specific degrees may not be mandatory. Practical skills, hands-on experience, and a strong understanding of machine learning concepts are often more crucial.

How important is hands-on experience in landing a Machine Learning job?

Hands-on experience is crucial for landing a machine learning job. Employers often value practical skills and the ability to apply theoretical knowledge to real-world problems. Working on projects, participating in competitions, and contributing to relevant repositories demonstrate practical expertise.

What is the future outlook for Machine Learning jobs?

The future outlook for Machine Learning jobs is promising. As industries increasingly leverage data for decision-making, the demand for machine learning professionals is expected to grow. Specialized roles in areas like computer vision, NLP, and reinforcement learning are likely to see increased demand.