Data Science And Machine Learning With Python, SQL, Tableau, Advance Excel & AWS (Bootcamp)

Key Outcomes

Python’s scope is nearly limitless. Data scientists, engineers, and developers are flocking to Python because it is versatile for applications ranging from web development to data science and from artificial intelligence to cybersecurity. In this program, you will learn the essentials of Python coding:

Identify, interpret, and apply core programming building blocks in Python code.

Use algorithmic thinking to break up problems into smaller pieces and solve each piece individually.

Recognize and apply best industry practices for programming.

Interpret, use, and build on existing code and Python libraries.

Program Modules

Data Science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data driven decisions has never been greater. This bootcamp will help anyone interested in pursuing a career in data science by teaching them fundamental skills to get started in this in-demand field.

The bootcamp consists of 8 weeks of live online courses that will provide you with the foundational skills required for Data Science, including open-source tools and libraries, Python, Statistical Analysis, SQL, and relational databases. You’ll learn these data science pre-requisites through hands-on practice using real data science tools and real-world data sets.

Upon successfully completing these courses, you will have the practical knowledge and experience to delve deeper in Data Science and work on more advanced Data Science projects.

Training Intro: Advance Data Analytics using SQL, Python, Statistics, Power BI and Tableau (Bootcamp)

A brief outline of the certificate:

• 6 hours per week for a 2 months duration

• Automated assessments and quizzes

• Repeat unlimited times at no additional cost

• Verified and Certified certificate

• 24×7 support to answer your queries and doubts

• Capstone project

• Resume/Interview preparation & Job placement assistance

Modules

WEEK 1: Learn Python

Introduction of Python

Operators in Python

Variables

Data Types

Conditions (if-else) (Python3- if, if-else, Nested-if)

Loops

Functions

Data Structures (for Python)

Exception Handling
WEEK 2: STATISTICS

Implementation of Mean, Variance, and Standard Deviation (in Python using NumPy)

Derivative and Function minimization

Probability Distribution

Set I – Uniform Distribution

Set II – Exponential Distribution

Set III – Normal Distribution

Confidence Interval

Covariance and Correlation

Random Variables (With Examples)

Hypothesis Testing

Basic Understanding

T-testing

Paired T-testing (detailed overview)

P-value in ML

F-Test

Z-test

Mathematical Explanation in ML

Chi-Squared Test for Feature Selection

ANOVA Test in Python

ANOVA Test using one-way

ANOVA using two-way
WEEK 3: SQL

Basics of relational databases

Basic Queries: SELECT, WHERE LIKE, DISTINCT, BETWEEN, GROUP BY, ORDER BY

Advanced Queries: CTE, Subqueries, Window Function

Joins: Left, Right, Inner, Full

Stored procedures and functions

Assignment
WEEK 4: MICROSOFT POWERBI

Understanding Business Intelligence

Understanding Power BI

Getting Started with Power BI

Getting Data in Power BI Desktop

Data Transformation

Introduction to Power Query (M Formula Language)

Data Modelling

Introduction to DAX

Data Visualization

Creating Custom Visuals

Visual Interaction

Exploring Filters

Creating Custom Slicers

Exploring Power BI Desktop Features

Power Bi service Features

Dashboard
WEEK 5: COUNTINUATION OF POWERBI
WEEK 6: TABLEAU

Understanding Tableau

Getting Started With Tableau

Getting Data in Tableau Desktop

Data Visualization

Creating Custom Visuals

Visual Interaction

Exploring Filters

Dashboard
WEEK 7: Data Pre-processing, Data Visualization, Exploratory Data Analysis

Overview of Data Visualization

Data Visualization with Python (includes use cases of libraries such as Matplotlib, Seaborn)

EDA in Python – Set I (basic techniques to analyze the data)

EDA in Python – Set II (basic visual techniques)

EDA on Iris Dataset (explanation of EDA & techniques involved for data visualization)

EDA using Seaborn – Titanic Dataset (explanation of EDA & techniques involved for data visualization)
WEEK 8: CAPSTONE PROJECT

Program Experience

Office Hours with Learning Facilitators

Demonstrations

Coding Exercises in Each Module

Bite-Sized Learning

Knowledge Checks

Dedicated Program Support Team

Mobile Learning App

Peer Discussion

Capstone Project

Bonus Content on Advanced Topics

Career Support

Certification & Digital Badge

Who Should Attend?

This online program is designed for anyone who is interested in acquiring programming skills in Python & Machine Learning. No prior programming knowledge is required.

Certificate

Upon successful completion of the program, participants will receive a digital certificate of completion from American Institute for IT Professionals. This is a training program, and it is not eligible for academic credit.