Masters In Data Analytics and Data Science with AI.

On completing this course, participants will gain expertise in data cleaning, exploration, and visualization techniques. They will also learn statistical analysis, and Machine learning modeling. Moreover, participants will gain proficiency in using popular data analysis tools such as Python, Excel , PowerBI , Tableau along with Data Science skills such as Model building and Computer Vision. These skills will enable them to make data-driven decisions and unlock the power of data-driven decision-making.

Get ready to embark on an exciting journey of discovering the limitless possibilities of data science and Data Analysis!

Objectives:-

After Python Programming python Course student will be able to:

• Scrap web site
• Data Cleaning and Visualization
• SQL developer
• Data Engineer
• Data Scientist Intern
• ML Engineer
• NLP Engineer
• JR Data Scientist
• CV Engineer
• RPA Developer
• Data Analyst
• Business Analyst
• Tableau Developer
• Power BI Developer
• Data Analyst Intern

Brief Contents (Syllabus)

Logic Building

• Introduction to programming languages
• Introduction to Algorithms
• Baseline for programming Language

Structured Query language (SQL)

Introduction to SQL

• What is Data and Database
• What is Database Management System
• What is SQL?
• SQL vs MYSQL

DDL & DML

• Data types, expressions, operators
• Data Definition Language (DDL)
• Creation of table
• Dropping a table
• INSERT statement
• UPDATE statement
• DELETE statement

DQL

• SELECT statement
• WHERE clause search condition
• Arithmetic, Comparison and Logical operator
• Range operator
• List operator
• Like operator
• Using ORDER BY, DISTINCT and TOP
• Using IS NULL and IS NOT NULL

Built in SQL Functions

• String Function
• Math Function
• Date Function
• Aggregate Function
• GROUP BY clause with HAVING
• HAVING VS WHERE

Joins and Sub query

• Introduction to Joins
• Types of Joins
• What are nested/sub queries
• Introduction Types of Sub-queries

Stored procedure and triggers and window functions

• Understanding meaning of stored procedure
• Creating first stored procedure using SQL
• What are triggers?
• Creating triggers for beginners
• Introduction to window functions

Dive into Excel

Introduction to Excel

• Understanding different ribbons and tabs
• Entering data
• Fonts , formatting , finding replacing values in excel

Dealing with dates , numbers and filters in excel

• Currency and date format
• Custom formats
• Sorting and applying filters on data
• Sorting data as per need

Excel Formulae

• Performing different calculations using excel formulae

Data visualization and reporting using excel

• Lookup and Reference
• Pivot Tables
• Charts
• What-if Analysis
• Intro to Macros

Tableau

Introduction to Tableau

• What is Tableau
• Architecture of Tableau
• Features of Tableau
• Installation of Tableau Desktop/Public
• Interface of Tableau (Layout, Toolbars, Data pane, Analytics pane etc)
• How to start with Tableau
• Top Chart in Tableau
• Introduction to the various file type
• Quick Introduction to the user interface in tableau
• How to create data visualization using Tableau feature “show me”
• Reorder and Remove Visualization Fields
• How to create calculated field
• How to perform operation using cross tab
• Working with workbook data and Worksheet

Organizing data using tableau

• Sort data
• Filter data
• Generating groups
• Building sets

Data Visualization/Graph

• Pivot table and Heat Map
• Highlight Table
• Bar Chart
• Line Chart
• Area Chart
• Pie Chart
• Scatter Plot
• Word Cloud
• Tree Map
• Blended Axis
• Dual Axis
• Reference lines
• Reference bends
• Trend lines

Dashboards and Actions

• Dashboard design
• Dashboards
• Dashboard actions
• Drilldown reports

PowerBI

Introduction to PowerBI

• Get Power BI Tools
• Introduction to Tools and Terminology
• Dashboard in Minutes
• Understanding PowerBi Desktop
• Connecting to a data sources

Dealing with Power Query

• Preparing data with query editor
• Merging and appending
• Case study on Sales analysis

DAX Query and data visualization

• Understanding syntax of DAX
• DAX functions
• Drawing different charts using PowerBI
• Creating and Manipulating with slicer
• Creating KPIs

l Case Study using PowerBi tools

Python Programming

• Python Installation and Basics
• Syntax and programming Structures
• Variables, Operators, Keywords, Expressions
• Decision Making: if, elif, else
• Loops: while, for, break, continue, pass
• List, Tuple, Dictionary, Set
• Functions, Modules
• Object Oriented Programming
• Exception handling
• File handling
• Regular expression (RegEx)

Libraries for data manipulation and data visualization

• Introduction to numpy and its functions
• Introduction to pandas and its functions
• Introduction to matplotlib and seaborn for data visualization

CASE STUDY -: IPL Data Analysis , Netflix and hotstar data analysis

Machine Learning

• Introduction to Machine Learning
• What is Machine Learning
• Applications of Machine Learning
• Supervised Vs Unsupervised Machine Learning
• Regression vs classification

Exploratory Data Analysis (EDA)

• Finding null values
• Detecting and removal of outliers
• Feature scaling – : Standardization and normalization

Introduction to Linear Regression

• What is regression?
• What is linear regression
• Building First ML model for marks prediction
• Simple linear regression
• Multiple Regression
• Polynomial Regression
• Error functions in Regression (MAE . MSE , RMSE )
• Calculating accuracy using R2Scor

CASE STUDY -: Car Price Prediction on cars24 dataset.

• Introduction to Overfitting and underfitting
• Overfitting Vs underfitting
• Bias-Variance Tradeoff
• Regularization Techniques -: Ridge and Lasso
• Understanding and demonstrating Ridge and lasso regression techniques.

Introduction to Logistic Regression:

• Sigmoid function
• Understanding parameters of logistic regression
• Confusion Matrix -: Precision , Recall , accuracy , f1 Score

Introduction to KNN

• Understanding working of K – Nearest Neighbors
• Advantages and drawbacks of using KNN

Introduction to SVM

• Understanding Support Vector Machine
• Hard and soft margin
• Understanding Support Vectors , Hyperplane
• Kernel technique

Decision Tree classifier

• Working of DT
• Gini Index and Entropy
• Pruning techniques
• Advantages and disadvantages of Decision Tree

Introduction to Ensemble learning

• What is Bagging and Boosting?
• Random Forest Classifier
• Introduction to boosting
• Unsupervised Machine Learning Algorithm
• Clustering
• K-means Clustering

Introduction to Deep Learning

• Artificial Neural Network (ANN)
• What is Deep Learning
• DL vs ML
• Forward and backward propagation
• Activation functions
• Optimizer
• Early stopping and dropout layer to handle overfitting

CASE STUDY – DIGIT CLASSIFICATION USING ANN

Introduction to Computer Vision

• Image pre-processing
• Detecting edges
• Understanding Convolutional layer and pooling layer
• Image classification using CNN
• Image Augmentation
• Reading text data from an image.

Case Study -: Hand gesture volume controller using MediaPipe

Case Study -: AI Exercise counter using MediaPipe

Certificate

• MIT Certification

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Note: We provide Industrial based training as we provide Engineering Design Services  under Milestone PLM Solutions PVT LTD.