Certificate Course on
DataScience With Python



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Learning Objectives
DataScience With Python

Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you will learn the essential concepts of Python programming and gain deep knowledge in data analytics, machine learning, data visualization, web scraping and natural language processing.

Python is a multi-paradigm or versatile programming language that can be considered as a sort of swiss knife for the coding world. This is because it supports structured programming, Object Oriented Programming and even functional programming patterns. The versatility of Python undoubtedly makes it the best-suited programming language for the data scientists. Here are some of the other advantages of python for data science, which will help you understand why you should learn data science with Python:

  • Python is a powerful open source programming language, which means that it’s free to use while having all the properties that a programming language should have.
  • It is a versatile programming language that supports Object-Oriented Programming, Structured Programming, and functional programming patterns.
  • Python has some 72,000 libraries in the Python Package Index that aid in scientific calculations and machine learning applications.
  • Python sports an easy to understand and readable syntax that ensures that the development time is cut into half when compared with other programming languages.
  • Python enables you to perform data analysis, data manipulation, and data visualization, which are very important in data science.

All the above-mentioned advantages of Python programming language make it ideal to be used for data science by the data scientists. Owing to the extensibility and general-purpose nature, it is recommended that you learn data science with Python.

Python is a required skill for many data science positions, so jumpstart your career with this interactive, interactive, hands-on course.

DataScience With Python

The Data Science with Python course will furnish you with in-depth knowledge of the various libraries and packages required to perform data analysis, data visualization, web scraping, machine learning and natural language processing using Python.

Python has surpassed Java as the top language used to introduce US students to programming and computer science, and 46 percent of data science jobs list Python as a required skill.

What Skills you will Learn

    This Python for Data Science training course will enable you to:

  • Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics
  • Install the required Python environment and other auxiliary tools and libraries
  • Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
  • Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions
  • Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave
  • Perform data analysis and manipulation using data structures and tools provided in the Pandas package
  • Gain expertise in machine learning using the Scikit-Learn package
  • Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline
  • Use the Scikit-Learn package for natural language processing
  • Use the matplotlib library of Python for data visualization
  • Extract useful data from websites by performing web scrapping using Python
  • Integrate Python with Hadoop, Spark and MapReduce
Frequently asked Questions
1. Who should attend this course?

There is a booming demand for skilled data scientists across all industries that make this course suited for participants at all levels of experience. We recommend this Data Science with Python training particularly for the following professionals:

  • Analytics professionals who want to work with Python
  • Software professionals looking to get into the field of analytics
  • IT professionals interested in pursuing a career in analytics
  • Graduates looking to build a career in analytics and data science
  • Experienced professionals who would like to harness data science in their fields
  • Anyone with a genuine interest in the field of data science
2. What type of Jobs we can expect after this training?

Upon completion of the Data Science with Python course, you will have the skills required to help you land your dream job, including:

  • IT professionals
  • Data scientists
  • Data engineers
  • Data analysts
  • Project managers
  • Program managers
3. What are the Pre-requisites for this Training?

There are no prerequisites for learning this course. However, knowledge of any one programming language and SQL will be beneficial

4. Who will provide the certification?

Upon successful completion of the Data Science with Python certification training, you will be awarded the course completion certificate from Kigyan

5. What are my system requirements?

The tools you will need to attend training are:

  • Windows: Windows XP SP3 or higher
  • Mac: OSX 10.6 or higher
  • Intel i3 with minimum 8 GB RAM
  • Internet speed: Preferably 512 Kbps or higher for online training
  • Headset, speakers, and microphone: you will need headphones or speakers to hear instructions clearly, as well as a microphone to talk to others. You can use a headset with a built-in microphone, or separate speakers and microphone
6. What are the training modes offered for this course?

We offer this training in the following modes:

  • Live Classroom training in our Training Centre
  • Live Virtual Classroom or Online Classroom: Attend the course remotely from your desktop via video conferencing to increase productivity and reduce the time spent away from work or home
7. Any Group Discount offered in this classroom training?

Yes, we have group discount options for our training programs. Contact us using the form on the right of any page on the website or send am mail with your requirement and the student count to Our customer service representatives can provide more details.

8. What payment options are available?

Payments can be made using any of the following options. You will be emailed a receipt after the payment is made.

  • Any Credit or Debit Card
  • Bank Transfer using NEFT / RTGS
  • Direct payment in our centre through cash / cheque
  • Online payment wallet like Google Pay, PayTM….
DataScience With Python
Introduction to Business Analytics
  • Types of Business Analytics
    • Descriptive
    • Diagnostic
    • Predictive
    • Prescriptive
  • Areas of Analytics
  • Business Decision Making
  • Business Intelligence (BI)
  • Data Science
  • Big data & Analytics
Introduction to Python
  •   Features of Python
  •   History of Python
  •   Installation of Python
    • Anaconda
    • Jupyter
    • Yhat
  • Modes of Python
    • Interpretation Mode
    • Batch Script mode
  • Indentation in Python
  • Writing Comments in Python Programs
Programming in Python
  • Types of Variables & Datatypes
    • String, Numeric & Boolean
    • Tuple
    • List
    • Dictionary
    • Set
  • Basic Operators
    • In, +,*
  • Functions
    • Built-in Sequence Functions
  • Control Flow in Python
    • If, Else, Elif
    • For Loops
    • While loops
    • Exception handling
Mathematical Computing with NumPy
  • NumPy Overview
  • Basics of NumPy
  • NumPy fundamental objects
  • Create and Print a NumPy array
  • Basic operators in NumPy
  • Shape manipulation & copy methods
  • Linear algebraic function
  • Writing Programs using NumPy
Scientific Computation with SciPy
  • Introduction to SciPy
  • Characteristics of SciPy
  • Sub Packages of SciPy
    • Optimization
    • Integration
    • Linear Algebra
    • Statistics
    • Weave
    • IO
Data Manipulation with Pandas
  • Introduction to Pandas
  • Data Structures of Pandas
  • Creating Series and Data Frames
  • Accessing elements form data structures
  • Vectorised Operations
  • Handling Missing Values
  • Analysing Data
  • Pandas SQL operations
Machine Learning with Scikit Learn
  • Introduction to Machine Learning
  • The machine Learning approach
  • Introduction to Scikit learn
  • Technologies for understanding a dataset
  • Supervised learning models
  • Unsupervised Learning models
  • Algorithms
    • Regression
    • Classification
    • Clustering
    • Directionality reduction
Natural Language Processing (NLP) with Scikit Learn
  • Introduction to NLP
  • How NLP is helpful
  • Modules to load contents and category
  • Feature extraction techniques
  • Approaches of NLP
Data Visulization with MATPLOTLIB
  • Introduction to Data Visualization & its inference
  • Why Python
  • Python libraries
  • Steps for Plotting
    • Line plot
    • 2D plot
    • Multiple plots
    • Sub plots
  • Types of Plots
  • Seaborn
Web scraping with Beautiful Soup
  • Introduction to Web scrapping
  • Web Scrapping Process
  • Introduction to Beautiful Soup
    • The Parsers
    • Objects
    • Tree
  • Various Operations on Tree
    • Searching
    • Modifying
    • Navigating
  • Parsing a Part of Document
  • Output- Formatting and Printing
  • Encoding
Python Integration with Hadoop
  • Hadoop Streaming – Python API
  • Mapper in Python
  • Reducer in Python
  • PySpark – Python API for Spark
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  • Getting moulding to the industry present requirement in hands of experienced and knowledge trainers... Proud to be a KIGYAN student...

  • Was very happy that we learnt something new which was unknown to us and had a good experience and the share of information was very clear and had a good sessions learning the topics