Business Analytics

Join LernzLab and embark on a transformative journey in Business Analytics. Our online courses equip you with essential analytical skills, combining core principles with advanced techniques. Gain expertise in data-driven decision-making, predictive modeling, and business intelligence. The best Business Analytics courses, like those offered in Delhi, go beyond technical skills by integrating real-world applications and strategic insights.

Course Highlights

100% Job Assistance

Hands-On Projects & Case Studies

5+ Industry Tools

Lifetime Access

Flexible Learning Hours

10+ Recognize Certificates

Course Description

  • What is Programming ?

  • Historical Evolution of Programming

  • What is Python ?

  • Features of Python

  • Fundamentals of Python Programming(Token, Operators)

  • Conditional Statements(if else, nested if else, elif)

  • Iterative Statements (for loop, while loop)

  • Functions in Python(Recursion, HOF, Lambda)

  • Collections in Python(List, Tuple, Dictionary, Set, String)

  • Modules in Python

  • File Handling and Exception Handling

  • OOPS Concepts

  • Multithreading

  • Database Connectivity

  • Arrays in numpy

  • Multi Dimensional Arrays

  • Operations on Array

  • Conversion of python object into numpy array

  • In-built functions to create an array

  • Insert, Update, Append, Merge, Reshape, Delete, Sort, Filter, Traversal etc.

  • Broadcasting and Vectorization

  • Series in pandas

  • Dataframe in pandas

  • Slicing and Splicing operations

  • Conversion of python object into Dataframe

  • In-built functions to create pandas

  • Import and Export Dataset (CSV, Excel, SQL)

  • Insert, Update, Append, Merge, Reshape, Delete, Sort, Filter, Traversal etc.

  • Introduction to EDA

  • Statistics

  • Types of Data

  • Data Profiling, Cleaning, Analysis

  • EDA using library built in datasets

  • Visualization using Seaborn

  • Visualization using Matplotlib

  • Feature Transformation

  • Feature Scaling

  • Feature Extraction

  • Feature Encoding

  • Feature Augmentation

  • Upsampling and Downsampling

  • Introduction to ML

  • Statistics

  • Supervised Learning

  • Regression Algorithms

  • Classification Algorithms

  • Unsupervised Learning

  • Clustering Algorithm

  • Introduction to Deep Learning

  • Statistics

  • Concept of Perceptron

  • Artificial Neural Network (ANN)

  • Forwardfeed and Backpropagation

  • Convolutional Neural Network (CNN)

  • Recurrent Neural Network (RNN)

  • Seq2Seq Model

  • LSTM and GRU

  • Attention Mechanism

  • AutoEncoder

  • Pre-Trained Models- GPT and BERT

  • Types of DBMS and its Terminology (Keys, ER-Diagram, Schema, Normalization etc)

  • Introduction about MySQL, SQL Server, PostgreSQL, Oracle, SQLite

  • Introduction to cloud-based SQL platforms (Amazon RDS, Azure SQL, Google Cloud SQL)

  • Types of Commands- DDL, DML, DQL, TCL, DCL

  • Operators, Clause and Constraints in SQL

  • Operations on database and tables

  • Sort, Filter, Merge, Copy, Backup and Restore, Import and Export etc.

  • Functions and Data Types

  • Subqueries and Nested queries

  • Joins, types of joins and Complex Queries

  • Advanced SQL Concepts (CTE, Indexes, Cursor, Window function, Procedures, Conditional Statements, Iterative Statements)

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Frequently Asked Questions.

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