Machine Learning Course in Patiala
Artificial Intelligence and data-driven technologies are rapidly disrupting industries. A Machine Learning Course in Patiala equips students and professionals with the practical skills needed to build predictive models, automate business processes, and solve real world issues using data.
- English
- English, Hindi
Upcoming Batch Weekdays!!!
Starting from Upcoming Weekend!
09:00 am – 1:00 pm Weekends
Fully Interactive Classroom Training
- 90 Hours Online Classroom Sessions
- 11 Module 04 Projects 5 MCQ Test
- 6 Months Complete Access
- Access on Mobile and laptop
- Certificate of completion
65,000 Students Enrolled
What we will learn
- Intelligence & Machine Learning
- Python for Machine Learning
- Data Preprocessing
- Supervised Algorithm
- Unsupervised Learning Algorithms
- Model Evaluation and Optimization
- Ensemble Learning Techniques
- Deep Learning Technologies (DLTs)
- Model Deployment Fundamentals
By enrolling in our Machine Learning course in Patiala, you will gain hands-on experience designing, training, evaluating and deploying machine learning (ML) models. Beginning with Python fundamentals and data handling before moving towards advanced algorithms, hyperparameter tuning and real world applications – everything will be covered during our 3-week program!
Who Can Go for a Machine Learning Course in Patiala?
This course is ideal for students and engineering graduates as well as working professionals such as Data Analysts, Software Developers and IT Professionals.
Aspiring AI & ML Engineers
Prior experience in mathematics, statistics or programming is helpful but not essential; all fundamental concepts will be covered from scratch to ensure optimal conceptual clarity.
Want to Discuss Your Roadmap to Become a Machine Learning Engineer in Patiala?
Our expert mentors offer personalized roadmaps tailored specifically to your career goals, which may include structured skill development plans, beginner to advanced project guidance and resume/portfolio creation as well as interview preparation and mock interviews before certification support and placement assistance.
With unlimited batch access, industry expert trainers, and flexible learning options – including unlimited batch access – and flexible learning options you can learn anytime from anyplace. Request a Call Back Now!
Advantages
Countless Batch Access
Industry Expret Trainers
Shareable Certificate
Learn from anywhere
Career Transition Guidance
Real-Time Projects
Industry Endorsed Curriculum
Interview Preparation Techniques
Class recordings
Course Mentor
Kushal Dwivedi
- 10 + Batches
- 4.8 Star Rating
- 859 Students Trained
- 450+ Successfully Placed
Hi, I’m Kushal Dwivedi, and I’m excited that you’re here.
Professionally, I am a Data Engineering mentor with strong industry exposure and hands-on experience in building scalable data solutions. I have successfully delivered 10+ batches and trained 859+ students, helping them understand data engineering concepts from fundamentals to advanced levels. With a 4.8-star rating and 450+ successful placements, I focus on practical learning, real-time tools, and industry use cases. In this course, you’ll learn how I combine real-world experience with structured, step-by-step teaching to help you build job-ready data engineering skills.
Machine Learning Course Content in Patiala
- Definition of Machine Learning
- Types of Machine Learning (Supervised, Unsupervised, Reinforcement Learning)
- Applications of Machine Learning
- Overview of the Machine Learning Workflow
- Linear Algebra Concepts
- Calculus Basics
- Probability and Statistics for Machine Learning
- Linear Regression
- Logistic Regression
- Decision Trees and Random Forests
- Support Vector Machines (SVM)
- k-Nearest Neighbors (k-NN)
- Model Evaluation Metrics (Accuracy, Precision, Recall, F1 Score)
- Cross-Validation
- Hyperparameter Tuning Techniques
- K-Means Clustering
- Hierarchical Clustering
- Principal Component Analysis (PCA)
- Association Rule Learning
- Basics of Neural Networks
- Perceptron and Multilayer Perceptron
- Backpropagation Algorithm
- Introduction to Deep Learning
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Transfer Learning
- Text Preprocessing
- Bag of Words Model
- Word Embeddings (e.g., Word2Vec, GloVe)
- Sentiment Analysis
- Image Processing Basics
- Convolutional Neural Networks for Image Classification
- Object Detection
- What is machine learning
- Different stages of ML project
- Supervised vs Unsupervised ML
- Algorithms in Supervised and Unsupervised learning
- Introduction to Sklearn
- Data preprocessing
- Scaling techniques
- Training /testing / validation datasets
- Feature Engineering
- How to deal with Categorical Variables – Dummy variables
- Categorical embedding
- Basics of Reinforcement Learning
- Markov Decision Processes
- Q-Learning and Deep Q Networks (DQN)
- Model Deployment Strategies
- Integration with Web Applications
- Model Monitoring and Maintenance
- Bias and Fairness in Machine Learning
- Ethical Considerations in AI
- Responsible AI Practices
What Our Students Say About Us
About Palin Analytics
Palin Analytics is a leading analytics and AI training institute committed to filling the void between academic study and industry expectations. Through hands-on sessions, live projects, and expert mentorship we equip learners for successful careers in Machine Learning and Artificial Intelligence.
FAQ's
A top Machine Learning course in Patiala should feature an industry-align curriculum, hands-on projects, experienced trainers and placement support. A program which incorporates real world case studies, Python training, model deployment and interview preparation may lead to greater career outcomes for those participating.
This course encompasses AI & ML fundamentals, Python programming, data preprocessing techniques for supervised and unsupervised learning, model evaluation with hyperparameter tuning capabilities, neural networks fundamentals, deep learning fundamentals as well as industry projects to give participants hands-on exposure.
Course duration typically spans 3 to 6 months depending on learning mode (weekend or weekday batches). Fees will depend upon curriculum depth, certification requirements and placement support support – please reach out directly for updated fee details.
Students, graduates, working professionals, software developers, and data analysts can enroll. While prior knowledge in mathematics or programming would be advantageous but isn’t essential as foundational concepts will be covered from scratch.
Yes, upon successful completion, this course provides shareable certification as well as resume development, mock interviews, career advice and placement assistance to assist learners in finding Machine Learning/AI roles.