Professional Certification Program in

Data Science & A.I

An Intensive Program backed with Real World Projects and Industry Experts to get you your Dream Job.

4.4/5 (1600+ ratings)

2500+ Enrolled Students

About the Course

Key Features

DataisGood gives you a platform that will leave no stone unturned in our bid to make you a Rockstar Data Scientist. We have meticulously planned your journey for a promising and fulfilling Data Science career ahead.

Curriculum

Module 1 : Introductory Content

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

PROJECT/ASSIGMENT

Excel Dashboard: Build a Dashboard to track the Sales for an Ecommerce Store. Help the Sales Manager to understand the Effectiveness of Product Sales in different Regions and Derive some Unseen Trends and Patterns that could help him to Maximize the Productivity.

Module 2 : Exploratory Data Analysis

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

PROJECT/ASSIGMENT

Players Performance Analysis: Analyze Performance metrics of players based on their skills, nationality, clubs, age etc to understand factors driving the performance of these players by using Pandas, Matplotlib, and Other Python Libraries learnt in this Module.

Module 3 : Data Wrangling

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

PROJECT/ASSIGMENT

Global Cost of Living: Answer the most common questions regarding living standards in different countries and understand the reasons behind them by Cleaning the Data Properly and Extensive Feature Engineering as the Data is in a Raw and Unconsumable Format.

Module 4 : Statistics and Hypothesis Testing

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.

Module 5 : Advanced Machine Learning

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.

Module 6 : Natural Language Processing

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

PROJECT/ASSIGMENT

Drugs Prescription using Consumer Reviews: Prescribe Drugs for Each of the Medical Conditions by using the Reviews given by the Patients who consumed the Drug and Find out Important Insights within the data using the Advanced NLP Techniques learnt in this Module.

Module 7 : Introduction to Deep Learning

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

PROJECT/ASSIGMENT

Fruits Identification System: Build and Train an Image Classifier which can Identify more than 50 different types of Fruits when shown in Real-time by using the Concept of Advanced Deep Learning Predictive Models especially the CNN Architectures.

Module 8 : API Building Model Deployment

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

PROJECT/ASSIGMENT

Precision Farming App: Build an App which can Achieve Precision Farming by suggesting Best Crops according to Climatic Factors to Optimize Agricultural Production by using Flask as Backend and then Deploy this Predictive Model on Heroku Server.

Module 9 : Tableau for Story Telling

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

PROJECT/ASSIGMENT

US Consumer Complaints Analysis: Build an Interactive Dashboard which can give a complete 360 degree Summary of the Dataset so that the Insights and Patterns can be utilized by the Team to Improve their Overall Consumer Experience and Satisfaction.

Module 10 : Big Data with Spark

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

PROJECT/ASSIGMENT

Chicago Crime Analysis: The Chicago Crime Dataset is Vast and Huge, Hence Analyzing the Data and Deriving the Insights become Impossible. Hence, Analyze this Data by using the Concept of Big Data and the Most Amazing Tool Spark which you have learnt in this Module.

Student Projects

Optimize the Investments Made by a Client using Statistics and Machine Learning

Tackling a Client Project, where you have to help the customer understand the Portfolio Management and Estimation of Risks using different statistical and Financial Models. Finally, You will help the Client to Optimize his Investments by Suggesting the most appropriate Portfolio.

Estimate the Lifetime Value for the Customers of an Ecommerce Giant

Build a machine learning predictive model to explain and articulate the lifetime validation and valuation for the customers who have ever Purchased or Visited the e-commerce Giant using advanced Statistical Techniques and Finally Help the E-Commerce Giant to understand the Value of each Customer.

Help the Medical Experts to Choose the Best Drug for each Condition using NLP

With Coming Age, Thousands of Drugs are coming for each Medical Condition, Making it very difficult for the Medical Professionals to keep themselves Updated about the Best of the Drugs. Using Advanced Text Processing and NLP Techniques help Identify the Best Drugs for each Medical Condition using the Patient Reviews.

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Capstone Project

The Capstone project will give you a taste of what data scientists go through in real life when working with data. It will allow students to create a usable/public data product that can be used to show your skills to potential employers.