Data science and Python Internships

Training is designed by industry professionals as per the industry requirements & demands.

Build a solid foundation by covering the most popular & and widely used tools & technologies.

 

 

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What you'll learn?

  • Master Data Science Fundamentals: Build a strong foundational understanding of data science and machine learning principles.
  • Real-World Experience: Gain practical insights through hands-on projects that replicate real-world scenarios.
  • Data Handling Proficiency: Develop expertise in data collection, cleaning, and preprocessing techniques.
  • Machine Learning Diversity: Explore a wide range of machine learning algorithms, encompassing supervised and unsupervised learning, regression, and classification.

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  • Deep Dive into Deep Learning: Delve into deep neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) for advanced tasks like image and natural language processing.
  • Model Deployment Mastery: Learn to deploy machine learning models in real-world applications effectively.
  • Tools and Frameworks Expertise: Work with industry-standard tools like TensorFlow and PyTorch, enhancing your skills in AI and ML development.

 

Curated Exclusively For Engineering Students

Requirements

  • Engineering students from 1st year through the final year of branches ECE,CSE, EEE,ISE  
  • Knowledgeable with basic C programming, Python
  • Hands-on experience in various tools

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Summary

Our Data Science Internship offers a comprehensive experience in the world of data science and machine learning. Gain hands-on knowledge, delve into real-world projects, and master the essential skills for data collection, preprocessing, and model development. Explore a wide spectrum of machine learning algorithms, including deep learning, and discover the art of deploying models for real-world applications. Join us to build a solid foundation in data science and embark on a successful career in this dynamic field.

Description

Our Data Science Internship program is designed to provide aspiring data scientists with a rich learning experience. During this internship, you will immerse yourself in the world of data science and machine learning, gaining practical insights and honing your skills.

Key aspects of our program include mastering the fundamentals of data science and machine learning, engaging in hands-on projects that replicate real-world scenarios, and developing expertise in data collection, cleaning, and preprocessing.

You will explore a diverse range of machine learning algorithms, from supervised and unsupervised learning to regression and classification. Additionally, our program includes a deep dive into advanced topics, including deep neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) for tasks like image and natural language processing.

A central component of your learning journey will be mastering the deployment of machine learning models in real-world applications, equipping you with practical skills that are highly sought after in the industry.

Throughout the program, you will work with industry-standard tools like TensorFlow and PyTorch, providing you with the proficiency needed for success in data science and machine learning. Join our Data Science Internship to build a strong foundation in this field and set yourself on the path to a rewarding career.

 

Detailed Curriculum: Modules

  • Overview of Data Science
  • Terminologies in Data Science
  • Applications of Data Science

  • Introduction to Python
  • Understanding Operators
  • Variables and Data Types
  • Conditional Statements
  • Looping Constructs
  • Functions
  • Data Structure
  • Lists
  • Dictionaries
  • Understanding Standard Libraries in Python
  • Reading a CSV File in Python
  • Data Frames and basic operations with Data Frames
  • Indexing Data Frame

  • Introduction to Statistics
  • Measures of Central Tendency I
  • Measures of Central Tendency II
  • Understanding the spread of data
  • Data Distribution
  • Introduction to Probability
  • Probabilities of Discreet and Continuous Variables
  • Central Limit Theorem and Normal Distribution I
  • Central Limit Theorem and Normal Distribution II
  • Introduction to Inferential Statistics
  • Understanding the Confidence Interval and margin of error
  • Hypothesis Testing
  • T tests I
  • T tests II
  • Chi Squared Tests
  • Understanding the concept of Correlation

  • What is Machine Learning?
  • Introduction to Machine Learning
  • Types of Machine Learning
  • Basic Probability required for Machine Learning
  • Linear Algebra required for Machine Learning

  • Introduction to Predictive Modelling
  • Understanding the types of Predictive Models
  • Stages of Predictive Models
  • Hypothesis Generation
  • Data Extraction
  • Data Exploration
  • Reading the data into Python
  • Variable Identification
  • Univariate Analysis for Continuous Variables
  • Univariate Analysis for Categorical Variables
  • Bivariate Analysis
  • Treating Missing Values
  • How to treat Outliers
  • Transforming the Variables
  • Basics of Model Building
  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • K-means
  • Data Set for Final Test

Tools Covered

py-spark
python (2)
jupyter
scipy (1)
numpy
matplotlib
tensorflow
sql
git
pandas

Testimonial

I completed my full stack developer internship from CITL vijaynagar For 1 month during which i have got good programing knowledge on python, django and web development. Good infrastructure with equipped lab facility skilled & well experienced trainers

 

T.HARIPRASATH

Student

I have completed my full python programing internship from CITL vijaynagar For 1 month during which i have got good programing knowledge on python, django and web development. Good infrastructure with equipped lab facility skilled & well experienced trainers

 

Bhuvan kumar R

Student

I have completed my python machine learning internship from citl vijaynagar for month during which i have got good programming knowledge on a concepts, I worked on 2 projects hand-on. As we gave project presentation we have improved our presentation & also communications skills and fr. are very helpful and friendly. Good Infrastructure with equipped lab facility skilled & well experienced trainers

 

Chethan.S

Student

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