Data Science Using Python

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Become a Data Scientist

Educonverge is the best providers of live online training for Data Science with Machine Learning course in Delhi NCR.

Data science is the new emerging field in today world with high growth and career perspective. It’s right time to move your career in data science by starting from basics of Data analytics and management to advanced topics like in Machine Learning with industrial case study. This course provides in-depth understanding of how data science integrates in various industrial verticals such as healthcare, banking, telecom, e-commerce, transportation and more.

Data Science with Machine Learning
( Professional Course )  Time : 40 hrs
Become a Data Scientist
Data science is the new emerging field in today world with high growth and career perspective. It’s right time to move your career in data science by starting from basics of Data analytics and management to advanced topics like in Machine Learning with industrial case study. This course provides in-depth understanding of how data science integrates in various industrial verticals such as healthcare, banking, telecom, e-commerce, transportation and more.
Introduction to Data Science
Duration
Module 1 2 hrs
Introduction to Data Science
Data Science Era
Data Science involvement in Industries
Business Intelligence vs Data Science
Data Science Life Cycle
Tools of Data Science
Introduction to Python
Introduction to Machine Learning
Module 2
Introduction to Python Programming
Introduction to Python
Basic Operations in Python
Variable Assignment
Functions: in-built functions, user defined functions
Condition: if, if-else, nested if-else, else-if
Module 3    2 hrs
Data Structure – Introduction
List: Different Data Types in a List, List in a List
Operations on a list: Slicing, Splicing, Sub-setting
Condition(true/false) on a List
Applying functions on a List
Dictionary: Index, Value
Operation on a Dictionary: Slicing, Splicing, Sub-setting
Condition(true/false) on a Dictionary
Applying functions on a Dictionary
Modules and Packages
Numpy Array: Data Types in an Array, Dimensions of an Array   2 hrs
Operations on Array: Indexing ,Slicing, Splicing, Sub-setting
Conditional(T/F) on an Array
Loops: For, While
Shorthand for For
Conditions in shorthand for For
Control statements
Shape Manipulation
Linear Algebra
Module 4 2 hrs
Python Pandas – Home
Python Pandas – Introduction
Python Pandas – Environment Setup
Introduction to Data Structures
Python Pandas – Series
Python Pandas – Data Frame
Python Pandas – Panel
Python Pandas – Basic Functionality
Function Application
Python Pandas – Reindexing
Python Pandas – Iteration
Python Pandas – Sorting
Module 5 2 hrs
Intro to Statistics
Statistical Inference
Terminologies of Statistics
Descriptive statistics
Statistical functions
Measures of Centers
Mean
Median
Mode
Measures of Spread
Variance
Standard Deviation
Histogram
Probability
Normal Distribution
Binary Distribution
Poisson distribution
Skewness
Bell curve
Hypothesis Building and Testing
Chi-Square Test
Module 6 2 hrs
Scientific computing with Python
SciPy and its Characteristics
SciPy sub-packages
Linear Algebra
SciPy sub-packages – Statistics
SciPy sub-packages – I O
Module 7 2 hrs
Data Analysis Pipeline
What is Data Extraction
Types of Data
Raw and Processed Data
Data Wrangling
Exploratory Data Analysis
Visualization of Data
MatplotLib
Bar Plot
Histogram Plot
Box Plot
Area Plot
Scatter Plot
Pie Plot
Seaborn
Module 8 2 hrs
Introduction to Machine Learning
Machine Learning Use-Cases
Machine Learning Process Flow
Machine Learning Categories
Module 9
Data Preprocessing
Data preparation
Intro to Scikit Learn
Module 10   2 hrs
Regression
Types
Algorithms
Linear Regression
Logistic Regression   2 hrs
Importance of Dimensions   2 hrs
Introduction to Dimensionality
Why Dimensionality Reduction
PCA
Factor Analysis
Scaling dimensional model
Implementation with Case Studies
Intro to Kaggle and UCI repository
Module 11 2 hrs
Classification
K-nearest neighbours
Metrics
Confusion Matrix
Classification report
Support Vector Machines 2 hrs
Working of SVM
Naive Bayes
Hyperparameter Optimization
Decision Tree Classifier
Entropy 2 hrs
Gini Entropy
ROC
AUC
Random Forest classifier
Linear Discriminant Analysis
Cross –validation
Implementation with Case Studies
Module 12   2 hrs
Unsupervised learning
Clustering Algorithms
K-Means Clustering
Hierarchical Clustering
Implementation with Case Studies
Module 13  2 hrs
NLTK Installation
Tokenize words
Tokenize sentences
Stop words in NLTK
Stemming words with NLTK
Speech tagging
Beautiful Soup  2 hrs
Tf-idf Vectorise
Sentiment analysis
Implementation with Case Studies
Module 14  2 hrs
Introduction to Artificial Intelligence
Introduction to Tensorflow
Implementation with MNIST Case Study
At the End implementation of any one of the projects could be assigned.
Projects :   4 hrs
1.      Customer churn prediction
2.      Bank fraud Loan Prediction
3.      Wine Type Prediction
4.      Titanic dataset
5.      Marketing channel sales prediction
Course Highlights :
Use Case Based study
Hands on Live Projects
Study material
Interview questions
Mock Interview

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Fee In India

 

Application Fees INR 0
Total Program Fees INR 30,000
The Program Fees can also be paid in installments
Registration  Fees INR 5000 (Non-Refundable)
First installment of the Program Fees

(Needs to Paid One Week Before the Batch Start Date)

INR 12,000
Second installment of the Program Fees

(Needs To Be Paid in the 6th Class)

INR 13,000
Discount on Program Fees: 10% Early Bird Discount valid till 16/03/19

10%  Extra discount on Lumsum Payment

Batch Closed:             17th Mar 2019

New Batch Starting:  30th March 2019 (Few Seats Left)

2nd Batch:                   07th April 2019

Admission Open Till: 29th March 2019 ( If Required Seats Filled, the admissions will be closed even before the Closing Date)

 

Fee In U.S.

 

Application Fees INR 0
Total Program Fees $ 500
The Program Fees can also be paid in installments
Registration  Fees $ 100 (Non-Refundable)
First installment of the Program Fees

(Needs to Paid One Week Before the Batch Start Date)

$ 200
Second installment of the Program Fees

(Needs To Be Paid in the 6th Class)

$ 200
Discount on Program Fees: 10% Early Bird Discount valid till 16/03/19

10%  Extra discount on Lumsum Payment

Batch Closed:             17th April 2019

New Batch Starting:  18th May 2019 (Few Seats Left)

2nd Batch:                   25th May 2019

Admission Open Till: 24th May 2019 ( If Required Seats Filled, the admissions will be closed even before the Closing Date)

 

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