Data Science and Machine Learning Internship Program Course

Data Science and Machine Learning Internship Program Course Course

A thorough internship-style program with live mentorship and significant project work

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Data Science and Machine Learning Internship Program Course on Edureka — A thorough internship-style program with live mentorship and significant project work

Pros

  • Full-stack DS/ML curriculum from Python to deep learning and visualization.
  • Strong real-world projects with end-to-end deployment and dashboards.

Cons

  • Higher cost compared to freely available DS resources online.

Data Science and Machine Learning Internship Program Course Course

Platform: Edureka

Instructor: Unknown

What will you learn in Data Science and Machine Learning Internship Program

  • Python & data analysis fundamentals: Master Python essentials, NumPy, Pandas, data visualization, probability, and statistics.

  • SQL & database management: Learn Microsoft SQL Server essentials including T‑SQL queries, stored procedures, concurrency, and relational database fundamentals.

  • Machine learning & model building: Explore supervised/unsupervised learning, regression, classification, time series, recommendation systems, and model tuning.

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  • Deep learning & NLP: Understand CNNs, RNNs, LSTMs, NLP pipelines, sentiment analysis, and build visualizations with Tableau.

  • Capstone & real-world projects: Build end‑to‑end projects such as movie recommenders, travel aggregators, heart‑disease predictors, HR systems, and Tableau dashboards.

Program Overview

Duration: Live instructor‑led over 4 months (~96 hrs)

Module 1: Python for Data Science

  • Topics: Python basics, NumPy, Pandas, data visualization, web scraping, probability/statistics, EDA.

  • Hands-on: Travel aggregator build + quizzes.

Module 2: Database Management

  • Topics: SQL basics, built‑in functions, T‑SQL, stored procedures, concurrency, interview prep.

  • Hands-on: HR management system project.

Module 3: Machine Learning

  • Topics: Supervised/unsupervised learning, recommendation engines, regression, classification, time series, evaluation metrics, hyperparameter tuning.

  • Hands-on: Heart disease prediction model.

Module 4: Deep Learning & Tableau

  • Topics: CNN, RNN, LSTM architectures, NLP preprocessing and modeling, Tableau dashboards.

  • Hands-on: DL model and visual analytics project.

Capstone Project

  • Project: Build a full end-to-end model (e.g., Netflix-style recommender) integrating data collection, modeling, evaluation, and visualization.

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Job Outlook

  • Career-ready roles: Prepares for roles like Data Scientist, Data Analyst, ML Engineer across industries.

  • Market-demand alignment: India expected to add 3M+ data roles by 2026—avg. pay ₹8 LPA, up to ₹30 LPA.

  • Certification & support: Live sessions, capstone, “Super Intern” recognition, and internship certificate available.

  • Portfolio advantage: Rich project portfolio helps for interviews and job placement.

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