Applied Data Science with Python by Simplilearn: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study, Virtual Classroom	Mode of Delivery Video and Text Based	Frequency of Classes Weekdays

Course overview

The Applied Data Science with Python Course has been developed to give candidates an in-depth understanding of the various Data Science techniques that can be performed using Python. The Applied Data Science with Python course uses real-life projects and case studies to impart learning.

The candidates can establish mastery in data science and analytics techniques using Python by enrolling in this Applied Data Science with Python Course by Simplilearn. Python has become a required and an important skill set for many data science positions in the industry, kick start your career with this interactive, hands-on, Data Science with Python Certification Training Course

Moreover, the Applied Data Science with Python Course online provides a comprehensive knowledge of the Python language and Python packages. You will be able to learn the various types of applied functions, gain an understanding of the data structure in Python, and perform data visualizations using the various libraries.

Once candidates complete the Applied Data Science with Python Course successfully, they will receive an industry-recognised certificate which has lifelong validity.

Course and certificate fees

Fees information

₹ 14,990 ₹19,990

The fees for course Applied Data Science with Python is -

Training Options	Fee
Self-Paced Learning	Rs. 14,990
Online Bootcamp	Rs. 15,990
Corporate Training	Available

certificate availability

Yes

certificate providing authority

Simplilearn

Who it is for

Software developer Data scientist

Candidates from all levels of experience can enrol in the course. Some common profiles include:

Analytics Professionals:
Software Developers:
IT Professionals:
Students Pursuing UG/PG Courses:

Eligibility criteria

Certification Qualifying Detail :

In order to get the certificate of completion, candidates must meet the following requirements:

For Online Classroom:

Must have attended one complete batch of Data Science Certification with R programming training
Must have completed 1 project

For Online Self-Learning:

Must have completed at least 85% of the course.
MUst have completed 1 project

What you will learn

Data wrangling Knowledge of data visualization Knowledge of python Knowledge of numpy

Gain in-depth knowledge of the many techniques that can be applied to the Data at hand
Get equipped with the means to design beautiful charts and graphs using Python’s built-in Data visualization libraries like Seaborn and Matplotlib
Learn to excel at Python which makes machine learning, deep learning, and predictive analytics a piece of cake
Work with NumPy and SciPy, Python’s mathematical computing libraries, which host a wide variety of mathematical and statistical tools
Use Scikit-learn to build models and realise Machine learning algorithms and techniques such as K-NN, dimensionality reduction, linear regression, logistic regression, clustering, and pipeline.
Use Pandas, Python’s foremost Data Manipulation tool to manipulate seemingly gibberish data into something legible and presentable

The syllabus

Lesson 1: Course Introduction

Learning Path
Program components

Lesson 2: Introduction to Data Science

Introduction
Data Science Process
Python for Data Science
Python Packages for Data Science
Types of Plots with Examples

Lesson 3: Numpy

Fundamentals of NumPy
NumPy: Array Object
Attributes of NumPy Arrays
NumPy Array Functions
Arithmetic Operations using
NumPy
Statistical Function in Numpy
String Function in Numpy
NumPy Array Indexing
NumPy Array Slicing

Lesson 4: Working with Pandas

Fundamentals of pandas
Data Structures
Introduction to Series
Introduction to pandas DataFrame
Introduction to Statistical
Operations in pandas
Date and TimeDelta in pandas
Date Handling in pandas
Timedelta in pandas
Categorical Data Handling
Text Data in pandas
Iteration
Sorting
Plotting with pandas

Lesson 5: Data Visualization

Introduction
Introduction to Matplotlib
Line Plot
Scatter Plot
Bar Chart
Box Plot
Radar Chart (Spider chart)
Area Plot
Polar Plot
Tree Map
Pie Chart
Matplotlib for 3D Visualization
Introduction to Seaborn
Plotting Graphs Using Seaborn
Violin Plot
Pair Plot
Heatmap
Joint Plot
Swarm Plot
Plotting 3D Graphs for Multiple
Columns Using Seaborn

Lesson 6: Maths and Statistics Fundamentals

Linear Algebra
Scalars and Vectors
Vector Operation
Norm of a Vector
Matrix and Matrix Operations
Rank of Matrix
Determinant of Matrix
Inverse of Matrix
Eigenvalues and Eigenvectors
Calculus in Linear Algebra
Importance of Statistics for Data
Science
Types of Data
Measures of Central Tendency
Measures of Dispersion
Measures of Shape
Covariance and Correlation

Lesson 7: Probability Distribution

Probability and Its Importance
Random Variable
Probability Distribution
Discrete Probability Distribution
Continuous Probability Distribution
Probability Density Function and
Mass Function
Cumulative Distribution Function
Central Limit Theoram
Bayes’ Theorem
Estimation Theory

Lesson 8: Advanced Statistics

Hypothesis Testing and Mechanism
Null and Alternative Hypothesis
Confidence Interval
Margin of Error
Confidence Levels
Z-Distribution (Standard Normal
Distribution)
T-Distribution
T-Test
Z-Test
Choosing Between T-test and
Z-test
P-Value
Chi-square Distribution
Analysis of Variance or ANOVA
F-Distribution
F-Test

Lesson 9: Data Wrangling

Introduction
Data Collection
Data Inspection
Dealing with Duplicates
Data Cleaning
Data Transformation
Data Binning
Handling Outliers
Merging and Joining Data
Aggregating Data
Reshaping Data

Lesson 10: Feature Engineering

Introduction
Feature Engineering Methods
Transforming Variables
Features Scaling
Label Encoding
One Hot Encoding
Hashing
Grouping Operations

Admission details

To get admission into Applied Data Science with Python course, make an online payment using following options:

Visa Credit or Debit Card
MasterCard
American Express
Diner’s Club
PayPal

Once payment is received, you will receive a payment receipt. You can access information via email.

Filling the form

step 1 - Visit the https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training

Step 2 - Click on Enroll now button

Step 3 - You will redirect to a new page

Step 4 - If applicants have a coupon then they need to apply this or click on the Proceed button.

Step 5 - Fill all the details such as name, email, and contact number, and click on proceed

Step 6 - At last pay the fee and save the receipt for future reference.

How it helps

Almost half of the Data science jobs today require proficiency in the Python programming language. The Applied Data Science with Python Course by Simplilearn will not only teach candidates the various tools of the platform but also help them apply those tools and techniques with an array of industry projects.

All in all, the course will get you ready for the evolving Data science industry, which is supposed to grow 15-fold in the coming 3-4 years. Once you complete the course, you can work as a Data Scientist or Analyst and earn a lucrative pay of INR 5 lakhs per annum.

FAQs

Will I receive a course completion certificate?

Once you complete the Applied Data Science with Python Course successfully, you will receive a course completion certificate.

How long is the certification valid for?

The Applied Data Science with Python Course by Simplilearn completion certificate has lifelong validity.

What is Python programming?

A high-level programming language, Python is mostly used in areas like web development and app development.

What will I learn by enrolling for Python for Data Science?

Python can be used for performing detailed data manipulation, data analysis, and data visualisation which makes it a mandatory tool to have for all the aspiring data scientists out there.