Data Science & A.I

Learn Fundamental Concepts of Excel to solve Daily Problems and Use Advanced Excel Techniques to Perform Data Analysis and Reporting by Creating Charts and Dashboards.

• Excel for Data Analysis
• Dashboarding and Storytelling
• What if Analysis and Optimization
• Statistical Modelling

Learn SQL for Querying Databases using Advanced SQL Statements and Clauses, and Python to Create Robust Solutions for Solving Complex Real World Problems.

• SQL Fundamentals
• Advanced Querying techniques
• Basics of Python Programming Language
• Functional  and OOPs Programming

Learn to Scrape and Extract Data from Various Sources and Use Regular Expressions, Numpy, Pandas for Solving Data Science Related Problems.

• Regular Expressions
• Introduction to Numpy
• Introduction to Pandas
• Introduction to Web Scraping

Perform Advanced Query Analysis using Pivot Tables, Cross Tabulations etc and Create Advanced Interactive and Animated Data Visualizations using Python.

• Basics of Data Analysis
• Query Analysis using Python
• Introduction to Advanced Data Visualizations
• Animated and Interactive Visualizations

Perform Exploratory Data Analysis, by using Advanced Profiling Tools, and Accordingly Process and Prepare the Data by using Advanced Data Cleaning and Feature Engineering Techniques.

• Introduction to Data Profiling
• Introduction to Data Cleaning
• Introduction to Data Manipulation
• Introduction to Feature Engineering

Learn Advanced Data Transformation, Data Processing and Data Mining Techniques to Handle Specific Cases of Structured and Unstructured Data Frame using Python Programming Language.

• Introduction to Data Transformations
• Introduction to Data Processing
• Introduction to Data Mining
• Introduction to Data Preparation

Learn Descriptive and Inferential Statistics to Gain an In Depth Understanding about the Data by using Advanced Statistical and Probabilistic Methods.

• Introduction to Descriptive Statistics
• Introduction to Inferential Statistics
• Introduction to Probability Theory
• Introduction to Normal Distribution

Perform Confirmatory Analysis or Hypothesis Testing to Confirm your Hypothesis by using Advanced Statistical Tests and Hypothesis Testing Tools.

• Introduction Hypothesis Testing
• Introduction to T-tests, Z-tests, F-tests
• Introduction to Chi-squared Tests
• Comparison of Statistical Tests

PROJECT/ASSIGMENT

Startups Case Study: Analyze the Indian Startups and Understand the Expanding Startups Ecosystem in India to answer some of the most Insightful and Interesting Questions by applying Different Types of Statistical Concepts learnt in this Module.

Apply and Implement Dozens of Advanced Statistical, Probabilistic, Deterministic, and Decision Based Machine Learning Models to Perform Predictive Analytics.

• Introduction to Statistical Modelling
• Introduction to Tree Based Models
• Introduction to Boosting Models and Ensembles
• Handling Imbalanced Datasets

Learn Clustering Analysis, Dimensionality Reduction Methods, Recommendation Engines, and Time series Forecasting Techniques to solve Interesting Problems.

• Introduction to Clustering Analysis
• Introduction to Dimensionality Reduction
• Introduction to Recommendation Engines
• Introduction to Time Series Forecasting

PROJECT/ASSIGMENT

Employee Promotion Prediction: Predict whether the employee deserves Promotion based on different attributes like Age, Training Score, Region, Department, Awards, KPIs, etc. by using the Advanced Predictive Modelling Techniques learnt in this Module.

Learn Advanced Natural Language Processing for Processing the Text Data and Gain Insights from it, which can be used for Predictive analytics and etc.

• Introduction to Text Processing
• Introduction to Text Cleaning Methods
• Introduction to Feature Engineering
• Introduction to Text Extraction Techniques

Solve Amazing and Interesting Use Cases and Problems using the Concepts from NLP such as Text Classification, Text Summarization, Topic Modelling etc.

• Introduction to N Grams Analysis
• Introduction to Text Classification
• Introduction to Text Summarization
• Introduction to Topic Modelling

Use Advanced Deep Learning Models to Solve Highly Computational and Complex Problems Including Data in Image, Video, Audio or any other Formats.

• Introduction to Artificial Neural Networks
• Tips and Tricks to Build Robust Neural Networks
• Introduction to Convolutional Neural Networks
• Introduction to CNN Architectures

Solve Advanced Problems using the Advanced Concepts using Supervised and Unsupervised Deep Learning Predictive Models and Computer Vision Technology.

• Introduction to Recurrent Neural Networks
• Introduction to LSTMs
• Introduction to Unsupervised Deep Learning
• Introduction to Computer Vision

Learn the Basics of Model Deployment and Deploy your AI Applications by using Flask as a Backend Tool and Heroku as a Server.

• Basics of Frontend
• Building APIs using Flask
• Backend Development using Flask

Build amazing Interactive and Useful Artificial Intelligence Based Applications by Deploying the ML and DL Models using Flask and Heroku

• Building Web Interfaces for Machine Learning Models
• Introduction to Model Deployment
• Deployment Flask Apps using Heroku

Learn Storytelling with Tableau to Create Highly Complex and Advanced Reports and Visualizations by adding Filters, Animations, Interactivity and Much More.

• Introduction to Basic Charts and Visualization
• Introduction to Mapping and Geospatial Visualization
• Introduction to Filters, LOD Expressions, and Table Calculations etc.

Learn to Perform Regression, Clustering and Forecasting using Advanced Scientific Functions, Also Create Dashboards and Storyboards using Tableau.

• Feature Engineering using Tableau
• Regression, Clustering, and Forecasting using Tableau
• Dashboarding and StoryBoarding in Tableau

Learn the Basic Concepts and Fundamentals of Big Data and Big Data Tools which can help you to Manage Big Data such as PySpark and Apache Spark.

• Introduction to Big Data
• Introduction to PySpark
• Introduction to Spark
• Basics

Know How to Handle Big Datasets by using PySpark and Apache Spark, Also Learn to Implement Machine Learning Models using Spark ML.

• Introduction to SparkSQL, and Data Frames
• Solving Complex ML Problems using Spark
• Machine Learning with Spark ML