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Data Analytics with Python Course & Training

Unleash the power of data with Data Science - uncover patterns, gain insights, and make smarter decisions for success.

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HOW WE Teach

Learn Data Science in
6 Months

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Why Choose Analytic Square ?

Enhance your career

Unlock limitless career opportunities in the dynamic field of Data Science

Expert Trainers

Expert trainers fueling your Data Science journey with knowledge and guidance

Lifetime Access

Get Lifetime access for classroom material for preprations and studeis.

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Student Life

At Analytic Square, students experience a vibrant academic environment, collaborating with like-minded individuals, engaging in hands-on projects, and gaining invaluable skills to excel in their data-driven journey

Learn & discover

Join Analytic Square, where learning becomes an exhilarating adventure, empowering you to explore, innovate, and unravel the endless possibilities of data science

Industry Specific Projects

Embark on industry-specific data science projects at our institute, gaining hands-on experience in sectors such as finance, healthcare, e-commerce, and more, to solve real-world challenges and drive impactful insights

Data Science with Python

  • 4 Months Duration
  • 1 on 1 Mentorship
  • Placement assistance
  • Real time projects
  • 24/7 Full support
₹ 40000
Full Course

Course Title: Data Science with Python

Module 1: Introduction to Data Science and Python

  • Overview of Data Science
  • Introduction to Python for Data Science
  • Setting Up Python Environment (Anaconda, Jupyter)

Module 2: Data Manipulation with Python

  • Introduction to NumPy and Pandas
  • Data Cleaning and Preprocessing
  • Working with DataFrame Operations
  • Handling Missing Data and Outliers

Module 3: Data Visualization with Matplotlib and Seaborn

  • Introduction to Data Visualization
  • Creating Plots and Charts with Matplotlib
  • Enhancing Visualizations with Seaborn

Module 4: Exploratory Data Analysis (EDA) with Python

  • Descriptive Statistics in Python
  • Data Distribution Analysis
  • Correlation and Heatmaps

Module 5: Introduction to Machine Learning with Scikit-Learn

  • Basics of Machine Learning with Python
  • Supervised Learning vs. Unsupervised Learning
  • Model Training, Testing, and Validation

Module 6: Regression and Classification with Scikit-Learn

  • Linear Regression
  • Logistic Regression
  • Decision Trees and Random Forests
  • Support Vector Machines

Module 7: Unsupervised Learning with Python

  • K-Means Clustering
  • Hierarchical Clustering
  • Principal Component Analysis (PCA)

Module 8: Introduction to Natural Language Processing (NLP) with NLTK

  • Working with Text Data in Python
  • Tokenization and Stop Words Removal
  • Sentiment Analysis with NLTK

Module 9: Introduction to Deep Learning with TensorFlow and Keras

  • Basics of Neural Networks
  • Building and Training Neural Networks with Keras
  • Convolutional Neural Networks (CNNs) for Image Classification

Module 10: Working with Real-world Datasets

  • Data Collection and APIs
  • Web Scraping with Beautiful Soup
  • Handling JSON and CSV Data

Module 11: Data Analysis with Pandas and SQL

  • Advanced Data Analysis with Pandas
  • Introduction to SQL for Data Analysis

Module 12: Data Visualization and Storytelling with Python

  • Advanced Data Visualization with Plotly
  • Creating Interactive Visualizations
  • Effective Data Storytelling

Module 13: Capstone Project

  • Applying Data Science Techniques to a Real-world Problem
  • End-to-end Data Analysis, Cleaning, Modeling, and Visualization
  • Presenting Project Results

TESTIMONIALS

What Our Students Say About Us

Our students rave about our data science institute! They appreciate the practical approach, supportive staff, and relevant curriculum. They feel well-prepared for real-world challenges and have successfully launched their careers in the field.

Their data science course covered all essential topics thoroughly.

Abhishek Kandwal

Data Scientist

The course was logically organized, allowing for smooth progression of knowledge.

Prakash Rajendran

Data Scientist

The course provided valuable insights and resources for launching my successful career in data science.

Vineet Sharma

Data Analyst

The course focused on practical skills that are in high demand in the industry.

Ansh Dhawan

Analyst

Classroom

Classroom training for data science provides hands-on experience, collaboration, and expert guidance

Online

Online training for data science offers flexibility, accessibility, and comprehensive curriculum

Trainer Help

The trainer's guidance in data science is invaluable for skill development

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