Class 01 | Overview of Data Science & Industry Use Cases

Class 1: Python Basics: Syntax, Variables, Data Types, Operators, Casting, Input, Comments

Class 2: Data Structures (List, Tuple, Set, Dictionary), Control Flow (If-Else, Loops), Problem-Solving

Class 3: Looping (For, While), Python Statements (pass, continue, break), Functions, Lambda, Math Module, Array

Class 4: OOP Basics: Classes, Objects, Inheritance, Iterators, Exception & File Handling

Class 5: Recap + Integrative Problem Solving

Class 6: Final Python Problem-Solving Class

Class 1: NumPy: Arrays, Indexing, Reshaping, Mathematical Ops, Joins, Splits

Class 2: Pandas: DataFrames, Importing, Cleaning, Filtering, Sorting, Merging, Missing Values

Class 3: Real-World Data Practice with Pandas

Class 1: Matplotlib: Line, Bar, Scatter, Histogram, Pie, Customization

Class 2: Seaborn: Relational, Categorical, and Distribution Plots, Countplot, Swarmplot, Real Dataset Plotting

Class 3: Data Visualization Project

Class 1: Git & GitHub: Repository Setup, Push/Pull, Collaboration

Class 1: Descriptive & Inferential Statistics, Probability

Class 1: Data Cleaning & Transformation

Class 2: Feature Engineering & Selection

Class 3: Real-World Preprocessing Project

Class 1: Machine Learning Algorithm

Class 2: Supervised Learning: Model Building(Regression), Model Evaluation for regression

Class 3: Supervised Learning: Model Building(Classification) , Model Evaluation for classification

Class 4: Unsupervised Learning: Clustering (K-Means, K-Modes, Hierarchical)

Class 5: Unsupervised Learning: PCA, Market Basket Analysis

Class 6: Hyperparameter Tuning, overfitting check, Data distribution check, Implement hypothesis testing

Class 1: Preprocessing (Tokenization, Stopwords, Stemming, Lemmatization), Bag of Words, TF-IDF, Word2Vec

Class 2: NLP Projects in English: Sentiment Analysis, Fake News Detection, Bullying Detection

Class 3: NLP Projects in Bangla: Comment Classification, Article Classification

Class 1: Intro to ANN, CNN, RNN, ANN for Structured Data

Class 2: CNN for Image Classification (CIFAR-10, Brain MRI, Handwritten dataset)

Class 3: CNN ( Customized dataset: Face Recognition), Fine-Tuning & Augmentation

Class 4: RNN/LSTM for Text Generation, Sequence Modeling, NLP Deep Learning Project

Class 1: LLM, RAG, Chatbot Concept

Class 2: practical

Class 3: practical

Class 1: Introduction to Databases & SQL for Data Science

Class 2: Creating & Managing Data

Class 3: Data Analysis with SQL

Class 4: Advanced SQL for Machine Learning

Class 5: SQL + Python Integration for Machine Learning

Class 01: Power BI Basics

Class 02: Data Loading & Transformation

Class 03: Data Modeling, Basic DAX and Starting Portfolio Project

Class 04: DAX Functions & Visualization Essentials

Class 05: Advanced DAX & Project Visualization

Class 06: Interactive & Map Visualizations

Class 07: Advanced Report Customization

Class 08: Finalizing & Deploying Project

Class 1: Final Project Planning, Dataset Selection, Model Building

Class 2: Final Presentation + Deployment Showcase