Applied Data Science with Python

BY
Simplilearn

Master the craft of data analytics machine learning, web scraping, Data visualization, and natural language processing with the Python language.

Mode

Online

Fees

₹ 14990 19990

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.

The highlights

  • 60+ hours of blended learning
  • 24 hours of self-paced, online learning
  • Interactive learning 
  • Jupyter notebooks integrated labs
  • Dedicated mentoring sessions from industry experts
  • 4 industry-based course-end projects

Program offerings

  • Blended learning
  • Corporate training
  • Interactive sessions
  • Course end projects
  • Self-paced learning
  • Jupyter notebooks integrated labs

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

NIL

certificate availability

Yes

certificate providing authority

Simplilearn

Who it is for

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 - Essentials of Python Programming

  • Introduction
  • Setting Up Jupyter Notebook: Part 1
  • Setting Up Jupyter Notebook: Part 2
  • Python Functions
  • Python Types and Sequences
  • Python Strings Deep Dive
  • Python Demo: Reading and Writing CSV Files
  • Date and Time in Python
  • Objects in Python Map
  • Lambda and List Comprehension
  • Why Python for Data Analysis?
  • Python Packages for Data Science
  • StatsModels Package: Part 1
  • StatsModels Package: Part 2
  • Scipy Package
  • Recap
  • Spotlight

Lesson 4 - NumPy

  • Introduction
  • Fundamentals of NumPy
  • Array Shapes and Axes in NumPy: Part A
  • NumPy Array Shapes and Axes: Part B
  • Arithmetic Operations
  • Conditional Logic
  • Common Mathematical and Statistical Functions in NumPy
  • Indexing and Slicing: Part 1
  • Indexing and Slicing: Part 2
  • File Handling
  • Recap

Lesson 5 - Linear Algebra

  • Introduction
  • Introduction to Linear Algebra
  • Scalars and Vectors
  • Dot Product of Two Vectors
  • Linear Independence of Vectors
  • Norm of a Vector
  • Matrix
  • Matrix Operations
  • Transpose of a Matrix
  • Rank of a Matrix
  • Determinant of a Matrix and Identity Matrix or Operator
  • Inverse of a Matrix and Eigenvalues and Eigenvectors
  • Calculus in Linear Algebra
  • Recap

Lesson 6 - Statistics Fundamentals

  • Introduction
  • Importance of Statistics with Respect to Data Science
  • Common Statistical Terms
  • Types of Statistics
  • Data Categorization and Types
  • Levels of Measurement
  • Measures of Central Tendency
  • Measures of Central Tendency
  • Measures of Central Tendency
  • Measures of Dispersion
  • Random Variables
  • Sets
  • Measures of Shape (Skewness)
  • Measures of Shape (Kurtosis)
  • Covariance and Correlation
  • Recap

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 - Pandas

  • Introduction
  • Introduction to Pandas
  • Pandas Series
  • Querying a Series
  • Pandas DataFrames
  • Pandas Panel
  • Common Functions in Pandas
  • Pandas Functions – Data Statistical Function, Windows Function
  • Pandas Functions – Data and Timedelta
  • IO Tools – Explain All the Read Functions
  • Categorical Data
  • Working with Text Data
  • Iteration
  • Sorting
  • Plotting with Pandas
  • Recap

Lesson 11 - Data Visualization

  • Introduction
  • Principles of Information Visualization
  • Visualizing Data Using Pivot Tables
  • Data Visualization Libraries in Python – Matplotlib
  • Graph Types
  • Data Visualization Libraries in Python – Seaborn
  • Data Visualization Libraries in Python – Seaborn
  • Data Visualization Libraries in Python – Plotly
  • Data Visualization Libraries in Python – Plotly
  • Data Visualization Libraries in Python – Bokeh
  • Data Visualization Libraries in Python – Bokeh
  • Using Matplotlib to Plot Graphs
  • Plotting 3D Graphs for Multiple Columns Using Matplotlib
  • Using Matplotlib with Other Python Packages
  • Using Seaborn to Plot Graphs
  • Using Seaborn to Plot Graphs
  • Plotting 3D Graphs for Multiple Columns Using Seaborn
  • Introduction to Plotly
  • Introduction to Bokeh
  • Recap

Lesson 12 - End to End Statistics Application with Python

  • Introduction
  • Basic Statistics with Python – Problem Statement
  • Basic Statistics with Python – Solution
  • SciPy for Statistics – Problem Statement
  • SciPy for Statistics – Solution
  • Advanced Statistics with Python
  • Advanced Statistics with Python – Solution
  • Recap
  • Spotlight

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.

Which companies recruit certified project management professionals?

Candidates will be able to apply and get hired in companies such as Amazon, Walmart, Oracle, Accenture, Microsoft, and many more.

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