Data Science & Machine Learning with Python

Start your Data Science Journey with this unique and Professional Certification program especially designed for Beginners and Working Professionals. You will be trained by expert Data Scientists in this 5 months weekend online format. You will start with programming in Python, will master the concepts of Data Science, and then will learn and understand Machine Learning along with Ensemble method and Recommender system. Finally you will work on 5 different real time projects and case studies. This program will also train you in Data Visualization with Tableau as well. Program also offers 3 mock interviews individually and placement assistance after completion of the course to make you ready for job interviews and the industry.

OnTutes Education
Created by OnTutes Education
Calendar
Upcoming Batch Starts From
31 Oct 2020
Calendar
Course Duration
5 months - Weekend Online Live Training Program
Data Science & Machine Learning with Python
₹ 36000
Zero interest EMI plans available
Deadline: 31 Oct 2020

This course includes

5 months - Weekend Online Live Training Program live lectures
5 projects
Full time access
Access on mobile and Tablet
Certificate of Completion
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What you'll learn

SQL for Data Science
Python for Data Science
Python Programming Fundamentals
Working with Data in Python
Statistics & Probability
Regression Analysis & Hypothesis testing
Data Analysis
Introduction to Numpy & Pandas
Data Visualizations
Exploratory Data Analysis
Seaborn
Machine Learning
Linear & Logistic Regression
K-Nearest Neighbors
Decision Tree and Random Forest
Support Vector Machines
K-Means clustering
Feature Engineering
Ensemble method
Recommender System
Tableau- Data Visualization

Tools & Technologies

This course is taught in Python programming language.

Course content

37 lectures
First Course for your Data Science Journey
Completely Online Live Lectures
Classes over Weekend
5 Live Projects with model solutions
1 Capstone Projects
Lectures recordings available after sessions
Online Shareable Certificate after completion of course
Mock interview Preparation help after completion of program
Python Programming Language based course
What is Data Science?
What is Machine Learning?
What is Artificial Intelligence?
Python Environment setup and Installation
Jupyter Notebook Overview
Spyder Overview
Weka Tool for Data Analysis and ML
Datatypes in Python-List / Dictionaries / Tuples / Sets
Functions, Procedure, lambda expressions, string slicing and dicing
Python comparison/logical operators
Loops and Conditionals statements
Object Oriented Concepts in python-Class/Object
Inheritance/Polymorphism
Python Special methods
Error and Exception handling
File operations in python
Python OS and SYS operations
Creating Python scripts for automation
Python practice exercises-Mini Project
Types of Data
Mean, Median, Mode
Using mean, median, and mode in Python
Variation and Standard Deviation
Percentiles and Moments
Types of Data Distribution and it’s graphical representation
Central Limit Theorem
Outliers and its effects in model building
Inter Quantile Range
Covariance and Correlation
Conditional Probability
Bayes’ Theorem
Probability Density Function
Probability Mass Function
Hypothesis Testing
Null Hypothesis / Alternate Hypothesis
Level of Significance / Confidence level
Degree of freedom
Statistical test,F-Statistic, T-Test, Jarque Bera test, Omnibus test
Numpy array Indexing, Operations
Matrix operations, arithmetic and scientific operations
Exercise on Numpy
1 question
Pandas Series usage
1 question
DataFrames in Pandas
1 question
Data manipulation using dataframe
1 question
Missing data treatment
1 question
Groupby using pandas
1 question
Data Input and Output using Pandas
1 question
Web scrapping using Beautiful soup
1 question
Connecting Database / XML and flat files
1 question
Understanding Uni,Bi & Multivariate Analysis
A Crash Course in Matplotlib
Implementation of Matplotlib on various datasets
Exercise on Matplotlib
Distribution,Categorical and Matrix Plot
Grids & Regression plots
Exercise with Seaborn’s library
Pandas Built in Data Visualization
Interactive Data Visualization using Plotly and Cufflinks
Introduction to Machine Learning
Linear Regression
Logistic Regression
K-Nearest Neighbors
Decision Tree and Random Forest
Support Vector Machines
K-Means clustering
Feature Engineering
Key Concepts in Machine learning
What is Ensemble method?
Recommender system in real time applications.
Exercise on recommender system with Python
Ecommerce Purchase order evaluations
Data Analysis on company HR dataset
Customer Analysis
Industry Projects using multiple Machine Learning Techniques
Building Artificial Neural Network for Churn Modeling using Keras
Building Convolution Neural Network -Image Recognition & Classification
Data Visualization in Tableau

Description

Start your Data Science Journey with this Certification program especially designed for Beginners and Working Professionals. Classes are held online every Saturday & Sunday for 2 hours for 5 months and training is done by expert Data Scientists.

Program offers 3 Mock Interviews individually after completion of the course to make you ready for job interviews and the industry.

After completion of this program, participants can apply for Advance level certification program.

Prerequisites:
  1. NA. This course can be taken by anyone who is interested in Data Science.
  2. Prior knowledge of programming will be a plus,but not necessary.
System Requirements:
  1. Laptop or desktop (min 4 gb RAM) with good speed internet connectivity
Course Delivery Mode:
  1. Instructor led Live lectures via online meetings.
  2. Recordings of the lectures will be available for your future references.
Minimum Eligibility Criteria:
  1. NA
Course Fee:

Course Fee: ₹ 36000

EMI plans available

Payment partners:
Zest Money
FAQs:

Please refer to the FAQ page for any more questions or raise a ticket here

About the instructor

OnTutes Education

OnTutes.com was founded with a mission to Celebrate Learning, helping professionals, students and learners upgrade their skill sets while evolving in sync with their chosen professional fields.