Big Data + Data Sciences Training with Machine Learning

Big Data + Data Sciences with Machine Learning (Complete Course)

Data Science is a new field that is just shaping up; hence all the confusion around what it really is. It is also a hybrid field that requires multiple skills and training. We felt that professionals thinking of getting into Data Science needed a primer in what this field is all about. Hence, we came up with this course. This is the most comprehensive Data Sciences and Machine Learning course will enable course participants to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow etc.

Course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms, course is designed for both beginners and experienced developers looking to make the jump to Data Science world. (online classes available)

What I will learn ?

Use Python for Data Science and Machine Learning
Implement Machine Learning Algorithms
Learn to use NumPy for Numerical Data
Learn to use Pandas for Data Analysis
Learn to use Matplotlib for Python Plotting
Learn to use Seaborn for statistical plots
Use MySQL For Data Handling
Final Project (Titanic DataSet)
Introduction To Big Data

Course Topics [ Comprehensive 4 Modules Course with Projects ]

Module-01 Data Sciences & Machine Learning Introduction

Introduction to Data Sciences & Machine Learning
Environment Set-Up
Jupyter Overview
Python Programming
Python 1st Project

Module-02 Data Analysis and Data Visualization using Python

Python for Data Analysis – NumPy
Data Analysis – Pandas
Data Analysis – Pandas Exercises
Data Visualization – Matplotlib
Data Visualization – Pandas

Module-03 Machine Learning

Introduction to Machine Learning
Linear Regression
Data Visualization – Seaborn
Data Visualization – Pandas Built-in Data Visualization
Data Visualization – Plotly and Cufflinks
Data Visualization – Geographical Plotting

Module-04 Analyzing Data with SQL

Introduction To SQL
Differentiate between RDBMS and NoSQL databases
Connecting sqlite with Python
Working on prepared datasets
Performing CRUD Operations

Module-05 Taking Overview Of Advanced Topics (Theory)

K Nearest Neighbors
Decision Trees and Random Forests
Support Vector Machines
K Means Clustering
Principal Component Analysis
Recommender Systems
Natural Language Processing
Neural Nets and Deep Learning

Module-06 Data Science Implementation Projects

Data Capstone Projects Overview
Finance Data Project Overview
Ecommerce Sales Analysis
Employee Salary Project
Movie DataSet Project Overview

Who should attend?

Senior Executives & Consultant drive key transformation projects for organization
Industry Professionals willing to develop a career in Big Data Sciences
IT Manager / Business Analyst / Data Analyst/ Data Scientist / Database Admin
Programmers / Software Developer / Anyone willing to start a career in Data Sciences

Educational approach

Lecture sessions are illustrated with case studies, practical questions, and examples
Practical exercises include Machine Learning, Data Visualization examples, and discussions
Install and Configure your Big Data, Machine Learning platform using industry famous tools
Project-based learning

International Student Fee : 600$