Python library Certified Course

Course Desription:

This Python Libraries course provides in-depth knowledge of the most widely used libraries essential for data analysis, automation, visualization, and machine learning. The course covers libraries such as NumPy, Pandas, Matplotlib, Seaborn, SciPy, Scikit-learn, TensorFlow, and more, enabling learners to efficiently handle data, perform computations, and build intelligent applications. With hands-on practice, real-time examples, and industry-oriented projects, students gain practical experience in using Python libraries to solve real-world problems. This course is ideal for students, professionals, and researchers who want to enhance their Python skills and apply them across data science, AI, and software development domains.

Key Features of Course Divine:

• Collaboration with E‑Cell IIT Tirupati
• 1:1 Online Mentorship Platform
• Credit-Based Certification
• Live Classes Led by Industry Experts
• Live, Real-World Projects
• 100% Placement Support
• Potential Interview Training
• Resume-Building Activities

Career Opportunities After Python library Certified Course:

• Python Developer
• Data Analyst
• Data Scientist
• Machine Learning Engineer
• AI Engineer
• Business Intelligence Analyst
• Automation Engineer
• Software Engineer
• Research Analyst
• Python Trainer / Instructor
• Backend Developer
• Data Visualization Specialist
• Freelance Python Developer
• Academic & Research Projects Assistant
• Startup & Product Development Roles

Essential Skills you will Develop Python library Certified Course:

• Python programming proficiency
• Data analysis and data manipulation
• Working with NumPy and Pandas
• Data visualization using Matplotlib & Seaborn
• Statistical analysis skills
• Machine learning fundamentals
• Model building and evaluation
• Automation and scripting skills
• Problem-solving and logical thinking
• Handling real-world datasets
• Debugging and error handling
• API and library integration
• Analytical and critical thinking
• Industry-ready coding practices

Tools Covered:

• Python (Core)
• Jupyter Notebook
• Anaconda
• NumPy
• Pandas
• Matplotlib
• Seaborn
• SciPy
• Scikit-learn
• TensorFlow
• Keras
• OpenCV
• PyCharm / VS Code
• Google Colab
• Git & GitHub

Syllabus:

Module 1: Python Basics Refresher Python syntax & data types Control structures Functions & modules File handling Exception handling.

Module 2: Working with NumPy NumPy arrays Array operations Indexing & slicing Mathematical functions Linear algebra basics.

Module 3: Data Analysis with Pandas Series & DataFrames Data cleaning & preprocessing Handling missing values Data aggregation & merging Import/export datasets.

Module 4: Data Visualization Matplotlib fundamentals Seaborn plots Customizing charts Statistical visualizations Dashboard-style plots.

Module 5: Scientific Computing with SciPy Optimization techniques Statistical functions Integration & interpolation Signal processing basics.

Module 6: Machine Learning with Scikit-learnv ML concepts & workflow Supervised learning algorithms Unsupervised learning Model evaluation techniques Feature selection.

Module 7: Deep Learning Basics Neural network fundamentals TensorFlow & Keras Building deep learning models Training & validation Performance tuning.

Module 8: Computer Vision with OpenCV Image processing basics Image transformations Face & object detection Real-time video processing.

Module 9: Automation & API Integration Automation using Python libraries Working with APIs Web scraping basics Data handling automation.

Module 10: Industry Projects & Case Studies Real-world datasets End-to-end project implementation Model deployment basics Best coding practices Interview preparation & career guidance.

Industry Projects:

• Data Analysis on Real-World Business Dataset
• Sales & Revenue Forecasting Project
• Customer Segmentation Using Machine Learning
• Stock Market Data Analysis
• Sentiment Analysis on Social Media Data
• House Price Prediction System
• Fraud Detection Model
• Recommendation System (Movies / Products)
• Image Classification Using Deep Learning
• Face Detection & Recognition System
• Automated Data Scraping & Reporting Tool
• Chatbot Using Python Libraries
• Time Series Forecasting Project
• Healthcare Data Analysis Project
• End-to-End Machine Learning Deployment Project

Who is this program for?

• Students and fresh graduates
• Engineering & science students
• Working professionals
• Data analytics aspirants
• Data science & AI beginners
• Software developers
• IT & non-IT professionals
• Researchers & academicians
• Automation & scripting learners
• Career switchers
• Freelancers
• Entrepreneurs & startup aspirants
• Python beginners with basic knowledge

How To Apply:

Mobile: 9100348679                   

Email: coursedivine@gmail.com