Internship in Data Science and Machine Learning

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



Data Science Internship


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)

  • 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

  • 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

  • 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 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

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

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

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

  • NumPy
  • Vectorized
  • Operation
  • Subsetting
  • Matrix Calculation

  • Pandas Series
  • Pandas Dataframe
  • Importing Data

  • Data Cleaning
  • Handling Missing Data

  • Creating graphs using Matplotlib
  • Customizing Plots
  • Saving Plots

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

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

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

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

  • Decision Tree Classifier
  • Support Vector Machine
  • KNN Classifier


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

Placement Statistics


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.



Duration: 1 month / 6 months
Enquire Now

Please Sign Up to Download

Enquire Now

Enquire Now

Please Sign Up to Download

Enquire Now

Please Sign Up to Download

Enquiry Form