Python programming
Internship 2024
Python is a versatile language with libraries like Pandas, NumPy, and Matplotlib for data analysis, visualization, and machine learning. It supports MySQL, NLP, statistical analysis, and deep learning through Keras, making it ideal for comprehensive data science and AI tasks.
1/ 2 Months
Online
8+ Live Projects
Dual Certification
Ultimate Step towards your Career Goals: Expert in Python Programming
Python is a versatile language with powerful libraries for data analysis, visualization, machine learning, and deep learning, making it essential for data science and AI.
Internship Benifits
Mentorship
Receive guidance and insights from industry experts.
Hands-on Experience
Gain practical skills in a real-world cutting-edge projects.
Networking
Connect with professionals and peers in your field.
Skill Development
Enhance your technical and soft skills.
Career Advancement
Boost your resume with valuable experience.
Certificate
Get a certification to showcase your achievements.
Python Internship Overview
Introduction to Python
- Basics, environment setup, and syntax.
Python – Tools, Syntaxes & Data Structures
- Overview of Python development tools, syntax, and foundational data structures (lists, tuples, sets).
Python – Dictionaries, Date, and Time
- Working with dictionaries, date, and time in Python.
Python – MySQL
- Connecting to MySQL, CRUD operations, and handling database queries.
Python – Date and Time, Data Wrangling
- Advanced date and time manipulations and data wrangling techniques.
Pandas Library – Introduction and Data Structures
- Introduction to Pandas, DataFrames, Series, and basic operations.
Python – Data Cleansing
- Techniques for cleaning and preparing data for analysis.
Pandas – Advanced Data Manipulations
- Filtering, merging, and aggregating data in Pandas.
Numpy Library – Introduction, Array Manipulations, Mathematical Functions
- Basics of Numpy, array manipulations, and mathematical functions.
I/O with Numpy
- Reading and writing data with Numpy for efficient handling.
SKLearn Library
- Introduction to Scikit-Learn and its main components for machine learning.
Python – Types of Distributions
- Common statistical distributions and their applications.
Python – Correlation, Chi-Square Test, Linear Regression
- Basics of correlation analysis, hypothesis testing, and simple linear regression.
Keras Library – Introduction
- Basics of the Keras library for neural network models.
Python – Word Tokenization, Stemming, and Lemmatization
- Text preprocessing techniques for NLP.
Matplotlib Library – Introduction, Pyplot API, and Types of Plots
- Basics of Matplotlib, using Pyplot, and creating various plots.
Matplotlib – Histogram Using Matplotlib
- Creating and analyzing histograms in Matplotlib.
Seaborn Library
- Introduction to Seaborn for enhanced data visualization.
Python – Data Visualization
- Techniques for visualizing data in Python for data storytelling.
Python – Statistical Analysis
- Overview of statistical concepts, distributions, and analysis methods.
Python – Data Wrangling and Data Cleansing
- In-depth data transformation and cleansing techniques.
Python – Statistical Analysis and Visualization
- Advanced visualization for data interpretation and insights.
Python – Data Wrangling, Data Cleansing
- Additional methods for data cleaning, handling missing data, and preparing data for ML.
Python – Types of Distribution, Correlation, Chi-Square Test
- Deeper exploration of distributions, statistical tests, and ML-ready data preparation.
Python – Linear Regression, Keras Library
- Building linear regression models and working with Keras for deep learning.
Looking for in-depth Syllabus Information? Explore your endless possibilities in Python with our Brochure!
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Project Submission: Example Output Screenshots from Our Clients
Take a look at these sample outputs crafted by our clients. These screenshots showcase the impressive results achieved through our courses and projects. Be inspired by their work and visualize what you can create!
Dual Certification: Internship Completion & Participation
Earn prestigious Dual Certification upon successful completion of our internship program. This recognition validates both your participation and the skills you have honed during the internship, providing a competitive edge in your professional journey. Show off your expertise with pride!
How does this Internship Program Work?
Step 1 Enroll in the Program
✅ Get a Mentor Assigned
✅Presentations & Practice Codes
✅ Learn at your Flexible Time
✅ Apprehend the concepts
Step 2 Project Development
✅ Implement Skills Learn
✅ Develop Projects with assistance
✅ Get Codes for Reference
✅ Visualise the Concepts
Step 3 Certification
✅ Get Certified
✅ Certificate of Internship
✅ Project Completion Certificate
✅ Share on social media
✅ Get Job Notifications
Internship Letter (LoR)
Internship Reports
Flexible Schedules
1 Month
₹1999/-
1 Month
- Internship Acceptance Letter
- 90 Days from the date of payment
- 4 LIVE interactive Mastermind Sessions
- 4+ Capstone Projects & Codes
- Full Roadmap
- Internship Report
- 1 Month Internship Certificate
₹3299/-
2 Month
- Internship Acceptance Letter
- 180 Days from the date of payment
- 4 LIVE interactive Mastermind Sessions
- 12+ Capstone Projects & Codes
- Full Roadmap
- Internship Report
- Participation Certificate
- 2 Month Internship Certificate
Our Alumni Employers
Curious where our graduates make their mark? Our students go on to excel in leading tech companies, innovative startups, and prestigious research institutions. Their advanced skills and hands-on experience make them highly sought-after professionals in the industry.
FAQ
What are the key features of Python?
Python is an interpreted, dynamically-typed, high-level language with a focus on readability and simplicity. It supports multiple paradigms, such as procedural, object-oriented, and functional programming.
What are the main data structures in Python?
Lists, tuples, sets, and dictionaries are the primary data structures in Python.
How do you get the current date and time in Python?
Use datetime.now() from the datetime module.
How do you connect Python to MySQL?
Use the mysql.connecter library or SQLAlchemy for ORM support.
What is Pandas used for?
Pandas is used for data manipulation and analysis, offering data structures like Series and DataFrames.
What is Numpy?
Numpy is a library for numerical computing in Python, providing support for arrays and matrix operations.
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