Machine Learning with Python CODE: RR-INT-MAC-010 Online

Machine Learning with Python Track

Build predictive machine learning models using Python, NumPy, Pandas, Scikit-Learn, Matplotlib, Seaborn, Feature Engineering, and Model Deployment.

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🛠️ Core Responsibilities

✓ Perform Exploratory Data Analysis (EDA) and data preprocessing.
✓ Train Supervised & Unsupervised Machine Learning algorithms.
✓ Evaluate model metrics (Precision, Recall, F1-score, ROC-AUC, RMSE).
✓ Deploy trained ML models as REST APIs using FastAPI / Flask.

🎯 Learning Outcomes & Skills Acquired

🚀 Mathematical & intuitive understanding of ML algorithms.
🚀 Feature engineering, handling missing data, and scaling techniques.
🚀 Productionizing ML models with FastAPI and Docker.

Key Technologies & Skills

⚡ Python ⚡ NumPy ⚡ Pandas ⚡ Scikit-Learn ⚡ Feature Engineering ⚡ FastAPI ⚡ ML Deployment

📅 Weekly Structured Training Plan

Week 1: Python for Data Science: NumPy Arrays & Operations

Week 2: Data Wrangling & Manipulation with Pandas DataFrames

Week 3: Exploratory Data Analysis (EDA) with Matplotlib & Seaborn

Week 4: Data Preprocessing, Imputation & Feature Scaling

Week 5: Supervised Learning: Linear & Logistic Regression

Week 6: Decision Trees, Random Forests & Ensemble Methods

Week 7: Support Vector Machines (SVM) & K-Nearest Neighbors (KNN)

Week 8: Unsupervised Learning: K-Means Clustering & PCA

Week 9: Hyperparameter Tuning (GridSearch, RandomizedSearch) & Cross-Validation

W10

Week 10: Model Evaluation Metrics & Handling Imbalanced Datasets

W11

Week 11: Building a Predictive ML API with FastAPI & Pickle/Joblib

W12

Week 12: End-to-End Machine Learning System Capstone Project

🎁 Program Inclusions & Evaluation

What Is Included & Completion Requirements

Detailed breakdown of the educational deliverables, mentor support, and certification criteria:

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Structured Educational Training

12 weeks of guided syllabus covering software engineering concepts, tools, and best practices.

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Direct Mentor Guidance

1-on-1 mentorship, code reviews, and architectural problem-solving guided by Rashesh Rehi.

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Hands-on Capstone Project

Build a production-ready application suitable for college submissions and portfolio showcases.

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Milestone Assessments

Regular milestone task evaluations to assess coding standards, problem solving, and architecture.

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Verifiable Certificate

QR-verifiable Digital Certificate of Training & Internship Completion upon meeting all criteria.

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Letter of Recommendation (LOR)

Performance-based recommendation letter endorsing your evaluated project quality and skills.

🎯 Completion & Credential Requirements:

Complete and submit all 4 required milestone tasks on the student portal.
Develop, document, and submit the functional capstone project source code.
Achieve passing evaluation from the mentor to qualify for Certificate and LOR issuance.

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Educational Program Transparency & Disclaimer

This program is an educational industrial training and project-based internship program conducted by Rashesh Rehi to help students build practical engineering skills and fulfill university curriculum requirements. It is an educational training program and does not constitute formal employment or an employer-employee relationship with any external company.

Track Overview

Fees: ₹999

Min Batch Size: 15 Students

Duration: 12 Weeks

Level: Beginner to Advanced

Language: English / Hindi / Gujarati

Mode: online

Stipend: Performance_based

Certificate: Available ✅

Recommendation Letter: Available ✅

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Rashesh Rehi

Founder & Principal Tech Lead • Rashesh Rehi Technologies

Senior Software Architect with 10+ years of industrial development experience guiding full-stack engineers and tech leads.