BUSINESS ANALYTICS COURSE TRAINING IN HYDERABAD

About LearnAi.co.in

LearnAI.co.in is a leading training institute committed to empowering individuals of all skill levels with comprehensive Business Analytics courses. Whether you're a beginner, intermediate, or expert, our expertly designed curriculum caters to your specific needs. Beginners are introduced to the fundamentals of business analytics, focusing on data analysis and visualization, while our intermediate courses delve deeper into statistical techniques and predictive analytics. For experts, we offer advanced modules covering machine learning, AI-driven decision-making, and big data analytics. With LearnAI.co.in, you can chart your own path to success in business analytics, all in a user-friendly and accessible learning format. Join us today to unlock your analytical potential.

Upcoming Batches

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What is Business Analytics?

Business analytics is like a superpower for businesses – it's the process of using data to discover insights and make smarter decisions. By analyzing information from sales, operations, and more, it helps companies understand their performance and plan for a successful future.

Why to learn Business Analytics?

Learning business analytics can supercharge your career growth by making you an invaluable asset to any organization. In today's data-driven world, professionals who can analyze and interpret data are in high demand, leading to diverse career opportunities and substantial earning potential. Don't miss out on the chance to stand out and excel in your career – start learning business analytics today!

Who can Pursue Business Analytics?

  • Any Degree pursuing or Graduated,
  • Bachelor’s, Master’s, PhD, and
  • Anyone interested in course
Enroll to Course Now

COURSE CURRICULUM

Python

  • Introduction
  • Installation
  • Fundamental of Python
  • Variables
  • Comments
  • Print Statement
  • Operators
  • Mutable Data Types
  • Data Types
  • Special Data Types
  • Conditions
  • Loops
  • Functions
  • Break, Continue and Pass Statements
  • String Object and working
  • List
  • Tuple
  • Set
  • Dictionaries
  • Map
  • Reduce
  • Filter
  • Classes
  • Objects
  • Inheritance
  • Multiple Inheritance
  • Modules
  • Error Handling

Data Visualization

  • Matplotlib
  • Seaborn
  • Plotly
  • Cuflinks
  • Bokesh

Libraries

  • Numpy
  • Pandas
  • Random
  • Math
  • Scipy
  • sklearn
  • Keras
  • Tensorflow
  • OpenCV
  • NLTK
  • Spacy
  • Lot more…

Tableau

  • Introduction to Data Visualization
  • Introduction to Tableau
  • Basics charts and dashboards
  • Special Char Types
  • Dashboard design and principles
  • Connections with servers
  • Local file access
  • Hands on experience with worksheet

Web Scraping

  • Url
  • Beautiful Soup

Data base

  • SQL
  • MongoDB

Statistics

  • Basics of Statistics
  • Descriptive Statistics
  • Inferential Statistics
  • Qualitative Analysis
  • Quantitative Analysis
  • Hypothesis Testing
  • Data Distribution
  • Probability Distribution
  • Normal Distribution
  • Poison Distribution
  • Outlier Detection
  • Other Statistical Fundamentals

Machine Learning

  • Supervised Learning
  • Unsupervised Learning
  • Semi Supervised Learning
  • Reinforcement Learning

Supervised Learning

  1. Regression Models
  2. Classification Models

Regression Models

  • Introduction to Regression Models
  • Linear Models
  • Linear Regression
  • Multiple Regression
  • Ordinary Least Square Method
  • Non-Linear Models
  • Support Vector Regressor
  • Random Forest Regressor
  • Decision Tree

Evaluation Metrics for Regression Models

  • R-Square
  • Adjusted R Square
  • Mean Square Error
  • Root Mean Square Error
  • Mean Absolute Error

Classification Models

  • Introduction to Classification Models
  • Logistics Regression
  • Naïve Bayes
  • Support Vector Classifier
  • K-NN Classifier
  • Decision Tree Classifier
  • Random Forest Classifier

Evaluation Metrics for Classification Models

  • Accuracy
  • Precision
  • Recall
  • F1 Score
  • ROC Curve

Unsupervised Learning

  • Introduction to Unsupervised Learning

Clustering Models

  • Introduction to Clustering Models
  • K- Mean Clustering
  • Hierarchical Clustering
  • High Dimensional Clustering

Dimension Reduction

  • Principal Component Analysis (PCA) Reinforcement Learning

Reinforcement Learning

  • Introduction to Reinforcement Learning

Featurization, Model Selection & Tuning

  • Feature Extraction
  • Model Defects & Evaluation Metrics
  • Model Selection and Tuning
  • Comparison of machine learning models

Neural Networks

  • Introduction to Deep Learning
  • Fundamental of Neural Networks
  • TensorFlow and Keras
  • Artificial Neural Networks (ANN)
  • Convolution Neural Networks (CNN)
  • Recurrent Neural Networks (RNN)
  • Evaluation of Deep Learning
  • Neural Networks Basics
  • Gradient Descent
  • Introduction to Perceptron & Neural Networks
  • Batch Normalization
  • Activation and Loss Functions
  • Hyper parameter tuning
  • SoftMax
  • Deep Neural Networks
  • Weights initialization

Image Pre-processing

  • Computer Vision
  • Open CV
  • Noise Detection
  • Noise Reduce
  • Low Pass Filters
  • Forward Propagation
  • Backward Propagation
  • Pooling & Padding

Natural Language Processing

  • Introduction to NLP
  • Corpus
  • Natural Language Understanding (NLU)
  • Natural Language Generator (NLG)
  • Tokenization (Word, Sentence, Blank, RegEx)
  • Frequency Distribution
  • Filtering
  • Stemming
  • Lemmatization
  • Stop Words
  • Regular Expressions
  • POS Tagging
  • Syntax Tree
  • Chunking
  • Lemmas
  • Hypernyms
  • Hyponyms
  • Synonyms
  • Antonyms
  • Distance Between words
  • Wordnet
  • Name Entity Recognition
  • Bag of words or Document Matrix
  • Count Vectorization
  • Term Frequency
  • Inverse Document Frequency
  • Sentimental Analysis

Job Roles

  • Data Analyst
  • Business Intelligence Analyst
  • Data Scientist
  • Financial Analyst
  • Market Research Analyst
  • Operations Analyst
  • Supply Chain Analyst
  • HR Analyst
  • Risk Analyst
  • Pricing Analyst
  • Healthcare Data Analyst
  • Sports Analyst
  • E-commerce Analyst
  • Digital Marketing Analyst
  • Environmental Analyst

Components of Business Analytics

  • Data Sources
  • Data Cleaning
  • Data Warehousing
  • Data Exploration
  • Statistical Analysis
  • Descriptive Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Data Visualization
  • Reporting
  • Machine Learning
  • Big Data Analysis
  • Business Intelligence Tools
  • Data Governance
  • Key Performance Indicators (KPIs)
  • A/B Testing
  • Time Series Analysis
  • Geospatial Analysis
  • Text Mining/NLP
  • Dashboard Development
  • Cloud Computing
  • Data Security
  • Domain Knowledge

What We Offer

24/7 Portal Access
Domain Expertise Trainers
Industrial Standard Course Structure
Job Oriented Programs
Recording Sessions
Assignments on Real time Scenarios
Job Support
Resume Preparations
Internships
Job Assistance
Working on Real Time Projects
Course Completion Certifications

We Provide Higher Quality Services

AND YOU’LL GET SOLUTIONS FOR EVERYTHING
Best Artificial Intelligence Training in Hyderabad with 100% placement Assistance. Learn Data Science with Python, Data Analysis, Artificial Intelligence, Machine Learning, Deep Learning, NLP, Statistics and Tableau.

Branches

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Phone: +91 9390023585
Email: info@learnai.co.in

Head Office

Address: 1st Floor, Rajadhani Theatre Complex, Pillar Number 1546, above Siri Mobiles, Dilsukhnagar, Hyderabad, Telangana 500060.
Phone: +91 9390023585
Email: info@learnai.co.in
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