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Data Analytics using Python


Price: 1,000 INR

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About Course

Python is a language that is very easy to learn even if you are a beginner and don’t have any programming background. It is well-worse with powerful libraries for machine learning, deep learning and AI which make it more powerful.

By the end of this course, you will have a solid foundation in Python for data analytics, as well as the skills to apply data analytics techniques to real-world problems. Whether you're a data analyst, business professional, or student, this course will provide you with the knowledge and skills you need to succeed in data analytics using Python.

Training sessions will be comprised of both exercises and lectures that will touch upon the topics mentioned in the Course Curriculum.

All our videos are recordings of our live training. We have intentionally kept discussions with participants in the videos to give you a feeling of the live training session.

What will You Learn?

 Introduction to Python

 Basic Operations in Python

 Data types in Python

 Concept of Looping

 Custom Function

 Use of Libraries like Pandas, Numpy, Matplotlib etc...

 Data Handling in Python

 Working with Data Frame (Using Pandas Library)

 Pivot Table in Python

 Descriptive Statistics

 Summarize data

 Data Visualization (Using Matplotlib Library)

Material Includes

  •   8+ Hours of High-quality Videos
  •   Exercise Files
  •  Handouts
  •  Unlimited Watch Time for 1 Year
  •  Verifiable e-Certificate

Requirements

 Anyone can Join

 Computer/ Laptop

 Devote time to perform tasks given during the sessions

Audience

 Business Analyst/ Data Analyst/ Data Scientist Aspirants

 Suitable for both beginners

 Students that want to be in the top 10% of Business Data Analysts

Meet your Instructor

Hiren Kakkad

CEO & Founder

Stat Modeller

  •  More than 10 years of industrial experience
  •  Awardee of the Training Quality Excellence Award by IQAC and ISTD
  •  Certified Trainer by NSDC & Skill India
  •  Certified by Google Analytics Academy for Data Studio
  •  Certified Lean Six Sigma Black Belt
  •  Trained 11000+ participants
  •  Guided 150+ Improvement projects
  •  Assisted 50+ Research Projects
  •  Trainer for in Data Analysis, R, Python, SPSS, Minitab, Power BI, Excel, Advanced Excel, Six Sigma, TPM, Kaizen, 5-S, Kanban etc.
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Course Curriculum

Introduction to Python
  • Welcome Note and Exercise Files
  • Welcome note and Faculty Introduction
  • Course Content
  • Why Python
  • Career Opportunities as a Python Programmer
  • Introduction to Python
  • Various IDEs for Python
  • Installation of Anaconda Distribution
  • Tour of Anaconda Interface
  • Important features of Jupyter
  • Tour to the Google Colab
  • How to organize data files
Data Types in Python
  • Understanding Data Types Part 1
  • Understanding Data Types Part 2
  • Practical on List in Python Part 1
  • Practical on List in Python Part 2
  • Q & A
  • Recap
  • Numeric Data Types Part 1
  • Numeric Data Types Part 2
  • Sequence Data Types - List
  • Sequence Data Types - String
  • Use of Brackets in Python
  • Sequence Data Types - Tuple
  • Boolean Data Types Part 1
  • Boolean Data Types Part 2
  • Set Data Type
  • Dictionary Data Type Part 1
  • Dictionary Data Type Part 2
Basic Operations
  • Arithmetic Operations in Python
  • Q & A
Custom Function
  • Recap
  • Define Custom Function Part 1
  • Define Custom Function Part 2
  • Define Custom Function Part 3
  • Define Custom Function Part 4
  • Common Syntax Error
  • Using Array in Python
  • Exercise - Create a Hotel Bill Calculator
  • Use Case of Custom Function
Working Directory
  • Package Vs. Module Vs. Function in Python
  • Setting up working Directory in Python
Data Handling
  • Import Data from CSV files
  • Accessing Specific Columns from the DataFrame
  • Data Slicing using iloc Function
  • Import Data from Excel File
  • Import Data from Website
  • Data Filtering in Python Part 1
  • Data Filtering in Python Part 2
  • Data Filtering in Python Part 3
  • Dealing with String Data
  • Find UNIQUE values in Python
  • Find NULL Value from the DataFrame
Pivot Table in Python
  • Pivot Table using Python Part 1
  • Pivot Table using Python Part 2
Scale of Measurement
  • Concept of Scale of Measurement
  • Scale of Measurement and Statistics
Basic Statistics
  • Recap
  • Basic Statistics Part 1
  • Basic Statistics Part 2
  • Basic Statistics Part 3
  • Types of Statistics
  • Measure of Central Tendency
  • When to use Mean, Median and Mode
  • Measure of Dispersion: Range, Variance and Standard Deviation
  • Importance of Standard Deviation
  • Concept of CV: Coefficient of Variation
  • Find Descriptive Statistics using Python
  • Difference between Percentage and Percentile
Groupby Function in Python
  • Find summary using GROUPBY Function
Concept of Looping
  • Concept of Looping: For Loop and While Loop
  • Using While Loop in Python
  • Using For Loop in Python
Conditional Statements
  • Concept of Conditional Statements: IF, ELSEIF, NESTEDIF
  • Conditional Statements: IF, ELSEIF, NESTEDIF using Python
  • Use Case of NESTEDIF in Python
Data Visualization
  • Data Visualization Understanding
  • Charts for Qualitative Data
  • Charts for Quantitative Data: Histogram and Boxplot
  • Charts for Quantitative Data: Scatter Plot
  • Overview of Matplotlib and Setup in Python
  • Bar Chart in Python
  • Clustered Bar Chart in Python
  • Pie Chart in Python
  • Histogram in Python
  • Boxplot in Python Part 1
  • Boxplot in Python Part 2
  • Scatter Plot in Python
  • Area Plot in Python
Export Analysis
  • How to Export Analysis
Session Wrap-up
  • Participants' Feedback
  • Thank you
FINAL EXAM
  • Exam Instructions
  • Final Exam
Feedback
  • Untitled Chapter
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London, UK

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