What you'll learn
Our Data Science Course is designed to help students and professionals build strong skills in data analysis, statistics, programming, machine learning, and business decision-making. This course teaches how to collect, clean, analyze, and visualize data to solve real-world problems using modern tools and techniques.
From basic concepts to advanced machine learning, you will learn step-by-step through practical projects, case studies, and hands-on exercises.
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Course Syllabus
Module 01
Introduction To Python
- Data Types & Variable
- Conditional Statement
- Loops In Python
- More On Data Types
- Object Oriented Programming
- Function And Modules
- File Handling
- Regular Expression & WebScraping
Module 02
Analysis with Python
- NUMPY
- Introduction To Matplotlib
- PANDAS
- Customizing Plots:
- Introduction To Seaborn Library
- Case Study
- IPL Data Analysis
Module 03
Diving Into Data And Statistics
- Visualising Data
- Characterising Data (Descriptive Statistics)
- Predicting From Data (Inferential Statistics)
- Craft Your Data
Module 04
Intro to Machine Learning And Advanced
- Machine Learning
- EDA Exploratory Data Analysis
- Linear Regression for ML
- Logistic Regression For Machine Learning
- Decision Tree
- Random Forests
- Ensemble Techniques
- Neighbours (K-NN) Alogorithms
- Support Vector Machines (SVM)
- Naive Bayes
- PCA – Principal Component Analysis
- K-means – Algorithms
- Hierarchical Clustering
Module 05
AI & Deep Learning
- Introduction To AI
- Introduction To Deep Learning
- Artificial Neural Network ANN Deep Dive
- Computer Vision CV
- Computer Vision With OpenCV
- Convolution Neural Network
- Natural Language Processing NLP
- Recurrent Neural Network RNN
- RASA Chatbot
- Introduction To Time Series Analysis TMS
- Weather Forecasting Using ARIMA Model
- Stock Price Prediction Using Sequence Model
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