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Data Scince Internship in Pune

Myinternship.in offers a comprehensive data science internship in Pune program for students and professionals looking to gain hands-on experience in the field of data science. The program is designed to provide participants with a thorough understanding of the various tools and techniques used in data science, as well as the practical application of these skills in real-world scenarios.

Throughout the internship, participants will work on a variety of projects under the guidance of experienced data science professionals. These projects will cover a range of topics, including data cleaning, data visualization, machine learning, and deep learning. Participants will also have the opportunity to work with real-world datasets and apply their newly acquired skills to solve real-world problems.

In addition to hands-on training, participants will also attend lectures and workshops on various data science topics, such as data analysis, data visualization, and machine learning. These sessions will be conducted by industry experts and will provide participants with a comprehensive understanding of the field of data science.


The data science internship in Pune program is open to students and professionals from a variety of backgrounds, including computer science, statistics, mathematics, and engineering. No prior knowledge of data science is required, but a basic understanding of programming and statistics is recommended.

At the end of the internship, participants will receive a certificate of completion and will have the opportunity to showcase their work to potential employers. The skills and experience gained during the internship will be highly valuable for those looking to pursue a career in data science or for those looking to gain a competitive edge in their current field.

If you’re looking to gain hands-on experience in data science and take your skills to the next level, Myinternship.in’s data science internship in Pune is the perfect opportunity for you. Apply now to join the program and start your journey to becoming a data science professional.


Module 01 : Python

Every data scientist needs to be knowledgeable about Python, which is both crucial and essential. Our experts will walk you through Python’s fundamentals and application areas in this section. Some of the most recent tools, including Numpy, Pandas, and Matplotlib, will be covered in this lesson.

          1. Environment set-up
          2. Jupyter overview
          3. Python Numpy
          4. Python Pandas
          5. Python Matplotlib

Module 02 : R

One of the more sophisticated statistical programming languages used in data science is R, which is used for statistical and data analysis. You will learn how to use R to explore data sets in this module. You will discover here –

          1. An introduction to R
          2. Data structures in R
          3. Data visualization with R
          4. Data analysis with R

Module 03 : Statistics

Understanding statistics is a critical ability that you must possess when working with data. In this lesson, you will learn:

          1. Important statistical concepts used in data science
          2. Difference between population and sample
          3. Types of variables
          4. Measures of central tendency
          5. Measures of variability
          6. Coefficient of variance
          7. Skewness and Kurtosis.
Module 04 : Inferential statistics

The application of inferential statistics allows for the generalization of sampled populations. This new area of statistics teaches you how to examine representative samples drawn from huge data sets. You will discover in this lesson –

          1. Normal distribution
          2. Test hypotheses
          3. Central limit theorem
          4. Confidence interval
          5. T-test
          6. Type I and II errors
          7. Student’s T distribution

Module 05 : Regression and Anova

You will learn how to construct a relationship between two or more objects after finishing this session. To examine the variations among sample sets, an analysis of variance, or ANOVA, is performed. You will discover here –

          1. Regression
          2. ANOVA
          3. R square
          4. Correlation and causation

Module 06 : Exploratory data analysis

In this lesson you will learn –

          1. Data visualization
          2. Missing value analysis
          3. The correction matrix
          4. Outlier detection analysis

Module 07 : Supervised machine learning

This thorough training will teach you how to programme computers or other devices to understand human language. You’ll discover –

          1. Python Scikit tool
          2. Neural networks
          3. Support vector machine
          4. Logistic and linear regression
          5. Decision tree classifier
Module 8: Tableau

Data visualisation is done using the sophisticated business intelligence tool Tableau. You will discover in this lesson –

          1. Working with Tableau
          2. Deep diving with data and connection
          3. Creating charts
          4. Mapping data in Tableau
          5. Dashboards and stories


Module 9: Machine learning on cloud

In this lesson, you will learn –

          1. ML on cloud platform
          2. ML on AWS
          3. ML on Microsoft Azure

These courses are all taught by professors with extensive backgrounds in data science and analytics. At the conclusion of the session, we help you with assessments and interviews in addition to providing you with one-on-one coaching.


Work on Real- Time Projects

Course Duration

1 Month/ 2 Months/ 3 Months/ 6 Months courses