DataScience Internship

 

🧠 Data Science Internship Program – 1 Month

Overview:

This intensive 1-month Data Science Internship is designed to equip students and early professionals with strong foundational and practical skills in the field of data analysis, data visualization, and machine learning. It combines theoretical learning with hands-on projects, using real-world datasets to simulate industry challenges.

Participants will gain expertise in Python, data wrangling, exploratory data analysis (EDA), and key machine learning algorithms, along with the ability to apply these skills to solve real-world problems.

📘 Program Highlights:

• Python programming tailored for data analysis
• Data cleaning, manipulation, and wrangling using Pandas & NumPy
• Visual storytelling using Matplotlib and Seaborn
• Introduction to supervised and unsupervised machine learning
• Real-time project implementation with datasets
• Resume & LinkedIn profile building for data roles
• Internship Certificate on completion

🔍 Week-wise Breakdown:

🔹 Week 1: Python & Data Handling

• Introduction to Data Science & Python
• Python syntax, variables, data types, and control structures
• Working with NumPy arrays and mathematical operations
• Pandas for data manipulation: reading data, filtering, grouping, cleaning

🔹 Week 2: Data Visualization & Exploratory Data Analysis

• Matplotlib: bar charts, line graphs, histograms
• Seaborn: heatmaps, pair plots, categorical visualizations
• Exploratory Data Analysis (EDA) – understanding data distributions, missing values, correlations
• Feature engineering and data preprocessing techniques

🔹 Week 3: Introduction to Machine Learning

• Understanding supervised vs. unsupervised learning
• Implementing Linear and Logistic Regression
• Decision Trees & Model Evaluation Techniques
• K-Means Clustering & use cases of unsupervised learning

🔹 Week 4: Capstone Project & Career Skills

• Choose & complete one real-time mini project:
• House Price Prediction
• Customer Segmentation
• Sentiment Analysis of Tweets
• Resume preparation with Data Science profile
• LinkedIn & GitHub setup for showcasing projects
• Final review & Certificate Distribution

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