Data Science
Course Curriculum
- What is Data Science? Use cases with business problems, ML solutions, roles, learning path, Q&A
- ML lifecycle: Problem → Data → EDA → Cleaning → Transformation → Model → Validation → Deployment
- Population, sample, data types, mean, median, mode, skewness, kurtosis
- Bar chart, box plot, scatter plot, correlation
- Python intro, installation, data types, operators
- List, tuple, set, dictionary, if-else conditions
- Loops, functions, NumPy arrays, pandas basics
- Data handling, groupby, merge, cleaning
- Matplotlib, seaborn, graphs, dataset analysis
- Probability, z-score, confidence intervals
- Z-test, t-test, significance level
- MLR, assumptions, multicollinearity
- Classification, confusion matrix, accuracy
- Precision, recall, F1, ROC, AUC
- Scaling, encoding, train-test split
- K-Fold, Stratified, Shuffle Split
- Underfitting, overfitting, feature engineering
- Hyperplanes, kernels, classification
- Gradient Boosting, XGBoost
- Project deployment basics
- Dimensionality reduction, eigen values
- K-means, DBSCAN, elbow method
- Collaborative & content-based filtering
- ARIMA, forecasting basics
- Perceptron, backpropagation, TensorFlow
- Text processing, TF-IDF, embeddings, NER
- LLMs, transformers, pretrained models
- Transformers, Hugging Face, real-world use cases
Core Python
- Python Introduction
- Programming Cycle of Python
- Python Installation
- Python IDE
- Variables
- Data Types
- Operators - Arithmetic, Comparison, Assignment, Logical, Bitwise
- List
- Tuple
- Set
- Dictionary
- If, If-Else, If-Elif, Nested If
- For Loop
- While Loop
- Break, Continue, Pass
- Defining Functions
- Calling Functions
- Function Arguments
- Return Statements
- Scope - Local & Global
- Lambda, Map, Filter, Reduce
- Importing Modules
- Creating User-defined Modules
- Python Standard Library
- Installing Packages using pip
- Importing Data
- Handling Missing Data
- Filtering & Filling Missing Data
- Data Transformation
- Removing Duplicates
- Data Type Conversion
- Outlier Detection (Boxplot, Z-score)
- Handling Outliers
- Feature Engineering
- Aggregation & Grouping
- Hierarchical Indexing
- Merging (merge, join, concat)
- Reshaping & Pivoting
- Datetime Conversion
- Extract Attributes
- Create Date Range
- Resampling
- Time Delta Calculations
- Time Zone Conversion
- Filtering by Date
- Try, Except, Else, Finally
- Built-in Exceptions
- Custom Exceptions
- Regex - match & search
- Patterns & Modifiers
- Class & Object
- __init__ Method
- Attributes & Methods
- Encapsulation
- Abstraction
- Iterators
- Generators
- Decorators
Tableau
- What is Tableau?
- What is Data Visualization?
- Tableau Products
- Tableau Desktop Variations
- Tableau File Extensions
- Data Types, Dimensions, Measures, Aggregation Concept
- Tableau Desktop Installation
- Data Source Overview
- Live vs Extract
- Overview of Worksheet Sections
- Shelves
- Bar Chart, Stacked Bar Chart
- Discrete & Continuous Line Charts
- Symbol Map & Filled Map
- Text Table, Highlight Table
- Formatting: Gridlines, Axes, Number Formatting, Shading, Row & Column Dividers, Marks Card
- What are Filters?
- Types of Filters
- Extract, Data Source, Context, Dimension, Measure, Quick Filters
- Order of Operations
- Cascading
- Apply to Worksheets
- Need for Calculations
- Types: Basic, LODs, Table Calculations
- Aggregate, Logical, String, Numerical, Date Functions
- LOD Examples
- Table Calculation Examples
- What are Data Combining Techniques?
- Types
- Joins, Relationships, Blending, Union
- Dual Axis
- Combined Axis
- Donut Chart
- Lollipop Chart
- KPI Cards (Simple)
- KPI Cards (With Shape)
- Groups - Purpose
- Bins - Purpose
- Hierarchies - Purpose
- Sets - Purpose
- Parameters - Purpose & Examples
- Reference Lines
- Trend Line
- Dashboard Overview - Tiled vs Floating
- Objects & Layout Overview
- Dashboard Creation & Formatting
- Actions: Filter, Highlight, URL, Sheet, Parameter, Set
- Publishing to Tableau Public
Mysql
- Introduction to Databases
- Introduction to RDBMS
- Normalization in RDBMS
- Types of RDBMS
- MySQL Workbench Installation
- Types of SQL Commands: DDL, DML, DQL, DCL, TCL
- Applications of SQL Commands
- Data Types: Numeric, Character, Datetime
- SELECT, LIMIT, DISTINCT
- WHERE: AND, OR, IN, NOT IN, BETWEEN
- EXISTS, IS NULL, IS NOT NULL
- Wildcards
- ORDER BY
- CASE WHEN THEN usage
- IFNULL and COALESCE
- GROUP BY and HAVING
- COUNT, SUM, AVG, MIN, MAX
- String Functions
- Date & Time Functions
- NOT NULL, UNIQUE, CHECK, DEFAULT
- ENUM
- Primary Key & Foreign Key
- Column Level & Table Level Constraints
- Inner Join
- Left Join
- Right Join
- Cross Join
- Self Join
- Full Outer Join
- Create, Drop, Alter
- Rename, Truncate
- Modify, Comment
- DML: Insert, Update, Delete
- TCL: Commit, Rollback, Savepoint
- Data Partitioning
- Types of Indexes
- Views in SQL
- IN Parameter
- OUT Parameter
- INOUT Parameter
- User Defined Functions
- Window Functions: Rank, Dense Rank, Lead, Lag, Row Number
- Union & Union All
- Intersect
- Subqueries
- Multiple Queries
- Exception Handling
- CONTINUE & EXIT Handlers
- Loops: Simple, Repeat, While
- Cursor
- Before Triggers
- After Triggers
