Machine Learning Course in Jaipur – Python, AI & Practical Projects
Build practical machine learning skills with Groot Academy’s Machine Learning Course in Jaipur. Learn Python, NumPy, Pandas, data preprocessing, visualization, Scikit-learn, regression, classification, clustering, ensemble learning, deep learning fundamentals, NLP, computer vision basics and machine learning deployment through hands-on projects.
What You Will Learn
- Python programming for machine learning
- Data preprocessing and exploratory data analysis
- Regression and classification algorithms
- Ensemble learning and model optimization
- Clustering and dimensionality reduction
- Model evaluation, cross validation and hyperparameter tuning
- Deep learning fundamentals with TensorFlow and Keras
- NLP and computer vision fundamentals
- Model APIs and deployment concepts
- Live projects and a final machine learning capstone
Related Courses
Also explore our Data Science Course in Jaipur, Artificial Intelligence Course in Jaipur, Generative AI Course in Jaipur, Python Programming Course in Jaipur and Data Analytics Course in Jaipur.
Practical Learning and Career Support
Work on practical projects through Live Project Training, explore Internship Programs and learn about Placement Assistance.
Frequently Asked Questions
Is this Machine Learning course suitable for beginners?
Yes. The course starts with Python and data fundamentals before progressing to machine learning algorithms and deployment concepts.
Which technologies are covered?
The course covers Python, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, Keras and basic Flask deployment workflows.
Are projects included?
Yes. Students work on regression, classification, clustering, NLP and end-to-end machine learning projects.
Curriculum
- 15 Sections
- 150 Lessons
- 4 Weeks
- Introduction to Machine Learning10
- 1.1Introduction to Machine Learning
- 1.2Machine Learning vs Artificial Intelligence
- 1.3Machine Learning vs Data Science
- 1.4Types of Machine Learning
- 1.5Supervised Learning
- 1.6Unsupervised Learning
- 1.7Reinforcement Learning Overview
- 1.8Real-World Machine Learning Applications
- 1.9Machine Learning Workflow
- 1.10Setting Up the Machine Learning Environment
- Python for Machine Learning10
- Data Preprocessing10
- Exploratory Data Analysis10
- 4.1Introduction to Exploratory Data Analysis
- 4.2Descriptive Statistics
- 4.3Data Distribution Analysis
- 4.4Correlation Analysis
- 4.5Feature Relationships
- 4.6Matplotlib Fundamentals
- 4.7Seaborn Fundamentals
- 4.8Creating Business and ML Visualizations
- 4.9Identifying Patterns in Data
- 4.10Exploratory Data Analysis Project
- Machine Learning with Scikit-learn10
- Regression Algorithms10
- Classification Algorithms10
- Ensemble Learning10
- Unsupervised Learning10
- Dimensionality Reduction10
- Model Evaluation and Optimization10
- Deep Learning Fundamentals10
- NLP and Computer Vision Basics10
- 13.1Introduction to Natural Language Processing
- 13.2Text Preprocessing
- 13.3Tokenization and Stop Words
- 13.4Text Vectorization
- 13.5Sentiment Analysis
- 13.6Introduction to Computer Vision
- 13.7Image Data Fundamentals
- 13.8Image Classification Concepts
- 13.9Machine Learning Applications in NLP and Vision
- 13.10NLP or Computer Vision Mini Project
- Machine Learning Deployment10
- 14.1Introduction to Model Deployment
- 14.2Saving Trained Models
- 14.3Pickle and Joblib
- 14.4Creating Prediction APIs
- 14.5Introduction to Flask
- 14.6Integrating Machine Learning Models with APIs
- 14.7Model Input and Output Validation
- 14.8Basic Deployment Workflow
- 14.9Introduction to Cloud Deployment Concepts
- 14.10Machine Learning Deployment Project
- Live Projects and Capstone Project10
- 15.1House Price Prediction Project
- 15.2Sales Forecasting Project
- 15.3Customer Churn Prediction
- 15.4Customer Segmentation Project
- 15.5Loan Prediction Project
- 15.6Spam or Sentiment Classification
- 15.7Recommendation System Concepts
- 15.8Machine Learning Model Deployment Project
- 15.9End-to-End Machine Learning Project
- 15.10Final Machine Learning Capstone Project
