Data Science Industrial Training Program

Description

Data Science is an interdisciplinary field that combines statistics, mathematics, programming, and domain expertise to extract valuable insights and knowledge from data. It involves analysing and interpreting large volumes of data to make informed business decisions, solve complex problems, and drive innovation. Data Science has applications in various industries, including finance, healthcare, marketing, and technology. The Data Science Fundamentals course provides students with a comprehensive understanding of the core concepts and techniques used in data science.

What you'll learn

Over 72 Lectures And 144 Hours of Content!

Theoretical And Practical Training Included Real-Time Projects.

Best Suitable for Beginners to Advanced Level Users and Who Learn Faster When Demonstrated.

Course Content Is Designed by Considering Current Trending Technologies and The Job Market.

Practical Assignments at The End of Every Session

Practical Real-Time Experience with Live Projects for Every End of The Topic.

Unlimited Resources, With Overall Six Courses LMS

Requirements

No Prerequisites required

Course Content

Introduction to Data Science Statistics Essentials for Data Science

Introduction to Data Science

Statistics Essentials for Data Science

Introduction to Calculus

Understanding the Data

Descriptive Statistics

Data Visualization

Probability

Probability Distributions

Sampling and Sampling Techniques

Inferential Statistics

Application of Inferential Statistics

Relationship Between Variables

Application of Statistics in Business

Program Refresher

Fundamentals of Programming

Introduction to Python Programming

Python Data Types and Operators

Conditional Statements and Loops in Python

Python Functions

Object-Oriented Programming Concepts with Python

Threading

Data Science with Python

Overview of Data Science

Python Environmental Setup and Essentials

Scientific Computing with Python (SciPy)

Data Manipulation with Pandas

Data Visualization in Python using Matplotlib

Data Analysis

Data Wrangling

Data Visualization

End-to-End Statistics Applications in Python

Introduction to Machine Learning

Introduction to Machine Learning and Artificial Intelligence

Data Preprocessing

Supervised Learning

Feature Engineering

Supervised Learning-Classification

Unsupervised Learning

Time Series Modelling

Ensemble Learning

Recommender System

Tableau

Core Tableau

Creating Charts in Tableau

Working with Metadata

Filters

Dashboard

Applying analytics

Modifications of Data Connections (LODS)

Business Analytics with Excel

Introduction to Business Analytics

Formatting Conditionals

Formatting and Important Functions

Analysing Data and Pivot Tables

Dashboarding

Business Analytics

Data Analytics

Introduction to SQL

Database Normalization and Entity Relationship Model

Working with Database and Tables

Working with Operators Constraints and Data Types

Functions

Triggers

Subqueries Operators and Derived Tables in SQL

Power BI

Introduction to Power BI

Get and Prep Data like a Super-Nerd

Develop Data-Nerd Prowess

Generating Reports and Dashboards, Tips and Tricks

Data Science with R

Introduction to R Programming

Data Structures

Data Visualization

Statistics for Data Science

Regression Analysis

Classification

Clustering

Association

Natural Language Processing

Introduction to NLP

Natural Language understanding Techniques

Natural Language Generation

Natural Language Processing Libraries

Natural Language with Machine Learning and Deep Learning

Introduction to Speech Recognition

Voice Assistant Devices Signal Processing

Projects

Uber Pickup Analysis

Conduct an Uber Pickup Analysis to evaluate and optimize pickup patterns and locations, using data analytics to improve operational efficiency and enhance user experience for ride-sharing services.

Building Chatbots

Create sophisticated chatbots to handle customer interactions and automate responses, leveraging natural language processing and machine learning to enhance user engagement and operational efficiency.

Audio Snowflake

Develop an Audio Snowflake system to visualize audio data in a unique, interactive format, using sound frequencies and waveforms to create detailed and dynamic visual representations of audio content.

Restaurant Success Prediction

Create a Restaurant Success Prediction model to evaluate potential restaurant performance based on various factors such as location, menu, and market trends, using data-driven insights to guide business decisions.

Stock Price Prediction

Develop a Stock Price Prediction model to forecast future stock prices using historical data and machine learning techniques, providing valuable insights for investment strategies and market analysis.

Road Lane Line Detection

Implement a Road Lane Line Detection system to accurately identify and track lane markings on roads, utilizing computer vision and image processing techniques to assist with autonomous driving and driver safety.

Wine Quality Prediction

Build a Wine Quality Prediction model to assess and predict wine quality based on chemical properties, utilizing machine learning techniques to provide insights for quality control and selection.

Music Generation

Create a Music Generation system that uses machine learning algorithms to compose original music, leveraging neural networks and data-driven models to produce melodies and harmonies.

Social Media Ads Analytics

Develop a Social Media Ads Analytics tool to analyze ad performance, track engagement metrics, and generate insights for optimizing marketing strategies across various social platforms.