Data Science Intern (Python, SQL, Pandas)
Skillfied Mentor Jobs India
Job Description
"Become a skilled Data Science Intern and unlock a world of opportunities in the field of data analysis and science."
As a Data Science Intern at Skillfied Mentor Jobs, you'll embark on an exciting journey to develop your skills in data analysis, machine learning, and data visualization using Python, SQL, and Pandas.
You'll have the chance to work with real-world datasets, build a strong foundation in data science, and collaborate with a team of experts to drive business decisions.
Why you should learn this:
The demand for data science professionals is skyrocketing, with a projected 14% growth in employment opportunities by 2028, according to the Bureau of Labor Statistics.
Expected Salary: As a data science intern, you can expect a competitive salary range of $60,000 to $80,000 per year, depending on your location and experience.
How it works:
- Step 1: Develop a strong foundation in Python, SQL, and Pandas through hands-on projects and real-world applications.
- Step 2: Learn data analysis concepts, including data cleaning, preprocessing, and exploratory data analysis (EDA), to uncover insights from complex datasets.
Core Concepts to Master
Data Cleaning and Preprocessing
Data cleaning and preprocessing are crucial steps in the data analysis process. You'll learn how to handle missing values, remove duplicates, and transform data into a suitable format for analysis.
Exploratory Data Analysis (EDA)
EDA is a technique used to summarize and visualize data to gain insights into its distribution, trends, and patterns. You'll learn how to use visualization tools, such as Matplotlib and Seaborn, to communicate insights effectively.
Data Modeling and Machine Learning
You'll learn the basics of data modeling and machine learning, including supervised and unsupervised learning algorithms, regression, classification, and clustering. You'll also learn how to evaluate model performance and optimize hyperparameters.
Interview Questions (Beginner)
- What is data science, and why is it important?
- How do you handle missing values in a dataset?
- What is the difference between supervised and unsupervised learning?
Job Overview
Advance Questions
- • How do you implement a recommendation system using collaborative filtering?
- • What is the concept of feature engineering, and how do you apply it?
- • How do you evaluate the performance of a machine learning model?