Welcome to AI Nexus IT Institute's Data Science Using Python Course!

Unleash the Power of Data with Python

Unlock the potential of data science and Python at AI Nexus IT Institute's comprehensive Data Science Using Python Course. Dive into the world of data analysis, visualization, and machine learning, and gain the skills that drive innovation in today's technology-driven landscape.

Discover the Art of Data Science

Harness the capabilities of Python to transform raw data into meaningful insights. From data manipulation to predictive modeling, our hands-on course empowers you to master the art of data science.

Explore Python Libraries

Leverage powerful libraries like Pandas, NumPy, and Matplotlib to manipulate and visualize data, creating dynamic visual representations that uncover hidden patterns.

Real-World Projects

Put theory into practice as you work on real-world data projects, honing your skills in a supportive and immersive learning environment.

Expert Guidance

Learn from experienced instructors who share their industry expertise, guiding you through every step of your data science journey.

Flexible Learning

Whether you're new to programming or an experienced coder, our course adapts to your skill level, ensuring everyone can excel in the world of data science.

Join us and become a data science innovator with Python at AI Nexus IT Institute

1. Data Power Unleashed: Turn raw data into actionable insights for smarter decisions.

2. Python Mastery: Analyze, visualize, and model data with Python expertise.

3. Real-World Learning: Tackle industry challenges through practical projects.

4. Dynamic Learning: Collaborate, build skills, and create a portfolio.

5. Ready for Careers: Preprocess, analyze, and visualize data for success.

6. Expert Guidance: Learn from experienced data professionals.

7. Flexible Learning: Access materials at your pace with support.

8. Diverse Paths: Open doors to data-driven roles.

9. Network Building: Connect and collaborate for valuable connections.

10. Tech Edge: Stay updated in the evolving data science landscape.

Enroll for a transformative journey into Python-powered data science.

Benefits of Data Science with Python course at AI Nexus IT Institutes

Key Features of Data Science with Python Course at AI Nexus IT Institute

1. Comprehensive Topics: Cover data science essentials - preprocessing, analysis, ML, visualization.

2. Real Projects: Solve industry challenges with practical projects.

3. Python Proficiency: Master coding for data manipulation and insights.

4. Expert Instructors: Learn from seasoned data professionals.

5. Interactive Learning: Engage with quizzes and assignments.

6. Flexible Formats: Choose self-paced or live sessions.

7. Tool Proficiency: Use Pandas, NumPy, Matplotlib, Scikit-Learn.

8. Effective Visualization: Communicate insights through visuals.

9. Machine Learning: Build predictive models, data-driven decisions.

10. Collaborative Environment: Connect for group learning.

11. Career Guidance: Prepare for interviews, build portfolio.

12. Latest Content: Stay updated with evolving methodologies.

Enroll for data-driven success in 'Data Science Using Python Course'.

Course overview

1. Introduction to Data Science:

Understand the fundamental concepts of data science and its real-world applications.

Explore the data science lifecycle and the role of Python in the process.

2. Python Essentials for Data Science:

Learn Python programming fundamentals and data structures required for data manipulation.

Gain hands-on experience in using Python libraries such as Pandas and NumPy for data analysis.

3. Data Manipulation and Preprocessing:

Discover techniques to clean, transform, and preprocess raw data for analysis.

Handle missing data, outliers, and data inconsistencies effectively.

4. Data Visualization:

Master the art of creating insightful visualizations using Matplotlib and Seaborn.

Communicate complex findings visually to stakeholders.

5. Statistical Analysis:

Explore statistical concepts and methods for drawing meaningful insights from data.

Perform hypothesis testing, correlation analysis, and more using Python.

6. Machine Learning Foundations:

Dive into the world of machine learning and understand its core principles.

Learn about supervised and unsupervised learning, and when to use each.

7. Building Predictive Models:

Build and evaluate predictive models using machine learning algorithms.

Implement regression, classification, and clustering techniques with scikit-learn.

8. Model Evaluation and Deployment:

Understand how to assess model performance and choose the right evaluation metrics.

Learn best practices for deploying machine learning models to real-world scenarios.

9. Capstone Project:

Apply your knowledge and skills to a hands-on capstone project.

Solve a real-world data science problem using Python and showcase your expertise.

Upcoming Batch Schedule

Course Duration: 4.5 Months

Here is schedule for our upcoming batches.

Upcoming New Batch : 5th Nov 2024 [offline]

Upcoming New Batch : 10th Nov 2024 [online]

AI Nexus IT Institute offers flexible timings for all students. The schedule for our upcoming batches includes weekday classes starting on the 1st and 15th of every month, from Monday to Friday. Additionally, we have weekend classes on the 1st and 15th of every month, held on Saturdays and Sundays. If this schedule does not align with your availability, please inform us, and we will make an effort to accommodate your flexible timings.

Quick Inquiry

🏆 Top 10 AI Data Science Trainers in India! 🏆

Our trainers aren't just ordinary educators; they're highly acclaimed in the field of data science and Python. Recognized by a leading magazine as the "Top 10 AI Data Science Trainers in India," they bring unparalleled expertise to the table. 🌟🇮🇳

🌟 Josh Talk Recognized! 🌟

But that's not all! They're also celebrated by Josh Talk, a platform that showcases the stories of India's most inspiring individuals. 🌟

Now, let's dive into their outstanding qualities:

🧠 Brains with Heart: Our trainers aren't just experts; they're passionate educators who live and breathe Python and data science! 💡

🎓 Data Wizards: They've mastered the art of data manipulation, turning raw data into golden insights! 📊

🤖 Machine Learning Maestros: With minds tuned to machine learning, they'll guide you through the AI jungle with ease! 🤖

📈 Visualization Virtuosos: They paint data stories that even Picasso would envy! 🎨

🌐 Python Gurus: Python isn't a language to them; it's their best friend in the digital world! 🐍

🔥 Passionate Educators: They're not just trainers; they're your mentors, igniting your data science passion! 🔥

🪄 Code Magicians: They'll show you the magic behind the code and help you conjure your Python spells! ✨

🗂️ Real-World Wizards: Their industry experience turns textbooks into practical, real-world solutions! 💼

👩‍🏫 Interactive Guides: They don't just teach; they immerse you in hands-on, interactive learning! 🙌

Join our course, and learn from India's best, recognized by both industry leaders and Josh Talk. Together, we'll unravel the world of data science using Python! 🌐🐍💫

Meet our Founder & Trainer of Data Science using Python Course

Successfully trained more than 5000 students across various domains

Data Science using python course curriculum

Module 1: Python for Data Analysis & Visualization (Weeks 1-3)

- Week 1: Introduction to Python for Data Analysis

- Python Basics: Variables, Data Types, and Operators

- Control Structures: If-Else, Loops

- Functions and Modules

- Week 2: Numpy Essentials

- Arrays, Basic Operations, Indexing, Array Processing

- Week 3: Pandas Mastery

- Series, Data Frames, Indexing

- Groupby, Concatenating, Merging

- Missing Values, Operations, Data Input and Output

- Pivot, Cross tab

- Week 4: Data Visualization with Python

- Introduction to Matplotlib

- Line plots, Histograms, Box and Violin Plots

- Scatterplot, Heatmaps, Subplots

- Visualization with Seaborn

Module 2: Understanding Text using Python (Weeks 5-6)

- Week 5: Working with Text Data

- Regular Expressions: Literals and Meta Characters

- Using Regular Expressions with Pandas

- Inbuilt Methods, Pattern Matching

- Week 6: Text Mining Project

- Data Collection, Mining, Pre-processing, Visualization

- Basic Statistics Terminology, Probability, Variables

- Central Tendencies, Probability Theory, Probability Distribution

Module 3: MACHINE LEARNING – SUPERVISED LEARNING (Weeks 7-11)

- Week 7: Introduction to Machine Learning

- Supervised Learning vs. Unsupervised Learning

- Regression Models: Linear and Multiple Regression

- Residual Analysis

- Week 8: Logistic Regression and Classification

- Logistic Regression

- Evaluation Metrics

- Naive Bayes Classifier

- Week 9: More Classification Algorithms

- K-Nearest Neighbor

- Decision Trees

- Support Vector Machine

- Week 10: Ensemble Methods and Case Studies

- Ensemble Learning

- Case Studies in Supervised Learning

- Week 11: Capstone Project and Career Preparation

- Work on a comprehensive capstone project

- Preparing for a career in Machine Learning

Module 4: MACHINE LEARNING – UNSUPERVISED LEARNING (Weeks 12-14)

- Week 12: Clustering Methods

- Clustering Algorithms

- Hierarchical Clustering

- Density-Based Clustering

- Week 13: Recommendation Systems and NLP Basics

- Recommendation Systems: Association Rules, Collaborative Filters

- Introduction to Natural Language Processing (NLP)

- Week 14: Advanced NLP Techniques

- Natural Language Understanding (NLP Statistical)

- Matrix Factorization, Text Indexing

- Text Classification and Case Studies

Module 5: Deep Learning and Neural Networks (Weeks 15-17)

- Week 15: Introduction to Neural Networks

- Perceptron, Activation Functions

- Deep Frameworks and TensorFlow Basics

- Week 16: Artificial Neural Networks

- Regression and Classification with ANN

- Convolutional Neural Networks (CNN) for Computer Vision

- Week 17: Deep Learning Frameworks

- Keras and Back-Propagation

Module 6: Model Deployment (Weeks 18-19)

- Week 18: Preparing Models for Deployment

- Creating pickle and frozen files

- Week 19: Cloud-Based Model Deployment

- Deploying Machine Learning and Deep Learning models for production

This comprehensive curriculum is designed to provide students with a well-rounded understanding of data science using Python. With hands-on projects, case studies, and an emphasis on practical application, learners will be equipped to excel in data-driven roles.

Note:-Copy of the detailed curriculum will be provided on enrollment of the candidates for the Data science course