Data Science Internship Program Overview
- This Data Science Internship Certification Program will help you master concepts like Python, Machine Learning, etc. Along with hands-on projects for better clarity on the topics. By the end of the internship, you will have the skills and knowledge to work as a Data Analyst, Data Scientist, or a Machine Learning Engineer. Join us today and take the first step towards a successful career in data science.
What topics will this Data Science Internship Program cover?
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- Fundamentals of Data and Data Science
- Introduction to Python
- Python Numpy
- Data Plotting and Matplotlib
- Installation of Python
- Data Structures
- Nested Loops
- Basics of Functions
- Introduction to OOPs
- Use cases of Data Science
- Introduction to Machine Learning
- Deploy a Project
Curriculum Designed by Experts
What is Data Science?
What does Data Science involve?
Era of Data Science
Life cycle of Data Science
Install Python IDE | IDE
Python Download and Installation on Windows, Linux and Mac
Execute the Script
Interactive and Script Mode
Python File Extensions
SETTING PATH IN Windows
Python Comments
What is Python?
Why Python?
How Python is used for Data Science?
Advantages or Disadvantages of Python
Run the Basic Program of Python
How to take an input from user?
Data Types: String, Numbers, Tuples, Lists, Dictionaires
Conditional Statements
Control Flow Statements
Syntax of function definition
Modules: What is a module?
Interpreted languages
Introduction to Numpy
Numpy Arrays
Quick Note on Array Indexing
Numpy Array Indexing and Operations
Exercise(s)
Introduction to Pandas
Series
Introduction of “ Data Frames ”
Organizing “ Data Frames ”
Set up “ Data Frames ”
Missing Data
Group by
Merging Joining and Concatenating
Operations
Data Input and Output
Exercise(s)
Introduction to Matplotlib
Matplotlib vs pyplot vs and pylab
Data For Matplotlib Plots
Create Your Plot
Play with Subplot
add_axes() and add_subplot()
Work with Size of Figures
Plotting Routines
Customizing PyPlot
Showing, Saving And Closing Your Plot
Exercise(s)
Introduction to Seaborn
Distribution Plots
Categorical Plots
Matrix Plots
Regression Plots
Grids: Style and Color
Exercise(s)
Introduction to Machine Learning
Machine Learning with Python
Supervised and UnSupervised Machine Learning
Exercise(s)
Linear Regression Theory
Model selection Updates for SciKit Learn
Linear Regression with Python – Part 1 Introduction
Linear Regression with Python – Part 2 Introduction
Linear Regression Project Overview and Project Solution
Exercise(s)
Logistic Regression Theory
Logistic Regression with Python – Part 1 Logistics
Linear Regression with Python – Part 2 Regression
Linear Regression with Python – Part 3 Conclusion
Logistic Regression Project Overview and Project Solution
Exercise(s)
K Nearest Neighbours Theory
K Nearest Neighbours with Python
K Nearest Neighbours Project Overview and Project Solution
Exercise(s)
Introduction to Tree Methods
Decision Trees and Random Forest with Python
Decision Trees and Random Forest Project Overview
Decision Trees and Random Forest Solutions Part 1
Decision Trees and Random Forest Solutions Part 2
Exercise(s)
SVM Theory
Support Vector Machines with Python
Support Vector Machines Project Overview
Exercise(s)
K Means Clustering Theory
K Means with Python
K Means Project Overview
Exercise(s)
Why to choose Prerogative’s Data Science Internship Training Program?
- Industry-recognized Data Scientist Certificate
- Pick project & Synopsis of your choice
- Practice Test, Assignments & Quizzes
- Online/Offline doubts & project support
- 24*7 Access to Assistance - Active Support Team
- Live-sessions while working with projects
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