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Data Science

Data Science and AI Programming using Python

A Comprehensive Journey into Data Science and AI Programming using Python.

Course Overview

Welcome to the exciting realm of AI, data science, and machine learning with Python! This course is meticulously designed to equip you with a robust understanding of programming, focusing on AI applications. From basic syntax to building complex machine learning models, explore the versatility of Python in the context of AI and data science.

Objective: Immerse yourself in the world of data science, machine learning, and AI programming using Python. This course provides a holistic approach, from mastering statistical concepts to advanced machine learning techniques. Gain hands-on experience in AI programming and set the foundation for a career as a Data Scientist.

Week 1: Statistics

  • Introduction to Statistics
  • Different types of Statistics
  • Population vs Sample
  • Mean, Median, and Mode
  • Variance, Standard Deviation
  • Variables and Random Variables
  • Percentiles & quartiles
  • 5-number summary
  • Histograms
  • Gaussian – Normal distribution
  • Standard Normal distribution
  • Application Of Z Score

Week 2: Data Manipulation and Visualization

  • Numpy
  • Pandas
  • Data Visualization with Seaborn and Matplotlib

Week 3: Exploratory Data Analysis (EDA)

  • Feature Engineering and Selection
  • Perform EDA with automated library

Week 4: Machine Learning Module – Basics

  • Introduction to machine learning
  • Difference between Supervised, Unsupervised Algorithms
  • Linear Regression
  • Logistics regression
  • Overfitting & Underfitting


Week 5: More on Regression and Performance Metrics

  • Ridge Regression
  • Lasso Regression
  • Logistics regression
  • Difference between Linear Regression and Logistic Regression
  • Performance metrics (Confusion matrix, F-beta Score)

Week 6: Machine Learning Module – Advanced

  • Decision Tree
  • Random Forest
  • SVM (Support Vector Machine)
  • K Nearest Neighbour

Week 7: Advanced Machine Learning Techniques

  • Ada boosting
  • Gradient boosting
  • XGBoosting

Week 8: Unsupervised Machine Learning

  • K-Means
  • Dimension Reduction Techniques (Principal Component Analysis – PCA)



This course caters to beginners with little to no programming experience, aspiring data scientists, and those eager to delve into AI using Python.

No, there is no age restriction. This course is suitable for anyone interested in pursuing a career in data science, machine learning, and AI programming.

A computer with Python and AI tools installed. Setup details will be provided at the beginning of the course.

Absolutely! Upon successfully completing the course, you'll receive a certificate recognizing your proficiency in Python, AI programming, and machine learning – valuable skills for a Data Scientist.

Enrollment is straightforward! Choose the course and follow the provided instructions. If you encounter any issues, our support team is ready to assist you. Embark on your journey into the dynamic world of data science and AI!

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