Internship in Data Science with AI ML

Eligibility: BE, B.Tech, ME, M.Tech

Intermediate

Overview

Introducing the 4-Week Data Science Internship Program by Cranes Varsity

Description

Cranes Varsity is offering 4-week Data Science Internship Program, aimed at providing aspiring
data scientists with hands-on experience and practical skills in the dynamic field of data science.

The Data Science Internship Program is a comprehensive learning journey that covers key topics
such as Python, data analysis, statistical modeling, machine learning, data visualization, and
predictive modeling. Through a combination of theoretical instruction, practical exercises, and
real-world projects, participants will gain valuable expertise in data-driven decision-making.
Under the guidance of experienced mentors, interns will work on cutting-edge data science
projects, gaining practical skills in data preprocessing, feature engineering, model development,
and evaluation. This hands-on experience will foster critical thinking, problem-solving abilities,
and collaboration skills.

Cranes Varsity believes in a holistic approach to learning, and interns will have access to
mentoring sessions, guest lectures, and interactive workshops. These opportunities will provide
insights into industry trends, best practices, and real-world applications of data science.

The 4-week Data Science Internship Program is open to students pursuing degrees in computer
science, statistics, or related fields. Prior knowledge of programming languages such as Python
will be beneficial.

By participating in this internship, students will gain a competitive edge in the data science job
market, equipped with both theoretical knowledge and practical experience. Cranes Varsity has a
strong track record of producing industry-ready professionals, further solidifying the value of
this program.

Benefits of this program

  • Internship with AICTE Registered company
  • Concept to Project experience
  •  Exposure to real time scenarios and challenges
  • Certificate of Participation

Data science became the most in-demand skill-set of the 21st century due to the increased amount of data generated by the online users and collecting same by most the companies, as data collected by these companies has to be utilized effectively to scale up the business, the need fora skilled data scientist is very high. The internship program in data science by cranes varsity provides the interns with a varied skill-set for one to master him/her self in the domain of data science.

During the internship program, the interns will get good exposure to Python programming concepts, Machine learning techniques and will also learn about the Project life cycle of data science. These skill-sets are learned to enable our interns to stand out during the interview process and can expect better job opportunities. Data Science is a very popular field and there are a ton of companies looking for people with this skill set. To give you just one example, we have over 700 open positions right now on our own platform, and that’s just one company! 

Course Objectives

  • Understanding language components, the IDLE environment, control flow constructs, strings, I/O, collections, classes, regular expressions and OOP
  • The course is supplemented with many hands on
  • Understanding the design & development of models using Machine learning
  • Understanding the design & development of models using Pandas , Matplotlib & Numpy

Tools and Resources

Python 3.8

Platform: Linux / Windows 7 and above

Course Content (Syllabus)

Control Flow

  • Relational Operators
  • if…else statement
  • if…elif…else statement
  • Logical operators
  • While Loops
  • break and continue statement
  • Loops with else statement
  • pass statement
  • Python for loop
  • Range Function

Lists

  • Creating List
  • Accessing elements from List
  • Inserting and Deleting Elements from List
  • List Slicing
  • Joining two lists
  • Repeating sequence
  • Nested List
  • Built-in List Methods and Functions
  • Searching elements in List
  • Sorting elements of List
  • Implementing Stack using List
  • Implementing Queue using List
  • Shallow and Deep copy
  • List Comprehensions
  • Conditionals on Comprehensions

Functions

  • Defining Functions in Python
  • Function Argument
  • Single Parameter Functions
  • Function Returning single Values
  • Functions with multiple parameter
  • Function that return Multiple Values
  • Functions with Default arguments
  • Named arguments
  • Scope and Lifetime of Variables
  • global specifier
  • Functional programming    tools:     map(), reduce() and filter()
  • Lambda: short Anonymous functions
  • Creating and importing modules
  • Programming Examples & Assignments
  • Recursion

Python Data Structures

  • Python Set
  • Creating Set
  • Adding/Removing elements to/from set
  • Python Set Operations : Union, Intersection, Difference and Symmetric Difference
  • Python Tuple
  • Creating Tuple
  • Understanding Difference between Tuple and List
  • Accessing Elements in Tuple
  • Python Dictionary
  • Creating Dictionary
  • Accessing / Changing / Deleting Elements in Dictionary
  • Built-in Dictionary Methods and Functions

Exception Handling

  • Understand Exception
  • Handling exception
  • try and except blocks
  • multiple except blocks for a single try block
  • finally block
  • Raising exceptions using raise

File Handling

  • Introduction to File handling
  • File opening modes
  • Reading data from file
  • Writing data to file

Object Oriented Programming

  • Creating Class
  • Creating Objects
  • Method Invocation
  • Understanding special methods
  •    init     method
  •    del     method
  •    str     method
  • Operator Overloading
  • Overloading arithmetic operators
  • Overloading relational operators
  • Inheritance

Module 1 – Data Analysis and Visulization

  • NumPy
  • Vectorized
  • Operation
  • Subsetting
  • Matrix Calculation

Pandas

  • Pandas Series
  • Pandas Dataframe
  • Importing Data

Data cleaning with pandas

  • Data Cleaning
  • Handling Missing Data

Matplotlib

  • Creating graphs using Matplotlib
  • Customizing Plots
  • Saving Plots

Module 2-Machine Learning

  • Understand what is Machine Learning
  • Supervised Learning
  • Unsupervised Learning

Introduction to Regression

  • Regression
  • Linear Regression with Single Variable
  • Multiple Linear Regression

Training Data Set

  • Training and Testing Data
  • Handling Categorical Data
  • K-Fold Cross Validation

Logistic Regression

  • Classification
  • Logistic Regression – Binary classification
  • Logistic Regression – Multiclass classification

Decision Tree

  • Decision Tree Classifier
  • Support Vector Machine
  • KNN Classifier

  • Python project development based onmatplotlib&pandas.
  • Python project development based onNumpy.

Projects

  • Python project development based on matplotlib &
  • Python project development based on

Placement Statistics

FAQs

Yes, Cranes Varsity training is available through online

 

Our Online training is Instructor-Led live online sessions

Yes, we will provide training course material for each module

Yes, we offer weekend classes as well evening classes.

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