![Data
Structures
• Strings
S= “Foobar”
Immutable
• Files
.text, .py, .xlsx, .csv
read, append, write.
• Lists
list = [“apple”, “banana”, “cherry”]
Ordered & Changeable.
• Dictionaries
No order, Lookup tag, Key-Value Pair
{“Money”: ‘Rupees’, ‘Dollar’, ‘Euro’}
• Tuples
a = (“Ankit”, “Arfana”, “Devesh”, “Kunal”)
Ordered, Immutable.](https://image.slidesharecdn.com/task-210309065532/85/Certified-Python-Business-Analyst-8-320.jpg)
Certified Python Business Analyst
- 4. Henry Harvin Analytics Academy Henry Harvin Analytics Academy has been setup with an objective to upskill the current technology and management workforce with in-demand analytics skillset. These skills are imparted through action oriented learning solutions that are carefully handcrafted by subject matter experts with extensive industry experience. These learning solutions are delivered using our unique goal-centric pedagogy by select professionals from leading organizations those also empaneled as domain experts with the academy. This enables the academy in achieving its goal of empowering aspiring analytics professionals to reach their full professional potential. Henry Harvin Analytics Academy aims to function in its outreach geographies and generate 50,000 employable analytics professionals till 2020 !
- 5. About the Course It was a 2 Months course of Business Analytics where I explore, Analyse & Solve Business Problems using Analytics Tools Python & Advanced Excel to analyze and forecast for a business/project to provide accurate results which could be used for decision making. Also we work on Real-life case studies using the statistical tools demonstrated, exercises and brainstorming using adaptive probing methodology. It helps to Get hands-on experience in applying analytics tools & techniques to real-world business problems and understand Analytics-Based Decision Making. Thus, become a Data Driven Professional.
- 6. Curriculum Module 1: Introduction to Analytics, Data & Analytics Module 2: Data Visualization Module 3: Machine Learning Module 4: Statistical Analysis, Framework to Solve Analytics Case Studies Module 5: Completion of Internship Project
- 7. Function of Python Business Analyst • Determine Organizational Goals • Mining Data • Data Cleaning. • Analyzing Data. • Pinpointing Trends and Patterns. • Creating Reports With Clear Visualization. • Maintaining Databases and Data systems.
- 8. Data Structures • Strings S= “Foobar” Immutable • Files .text, .py, .xlsx, .csv read, append, write. • Lists list = [“apple”, “banana”, “cherry”] Ordered & Changeable. • Dictionaries No order, Lookup tag, Key-Value Pair {“Money”: ‘Rupees’, ‘Dollar’, ‘Euro’} • Tuples a = (“Ankit”, “Arfana”, “Devesh”, “Kunal”) Ordered, Immutable.
- 9. Problem Statem Important Libraries In python – Machine Learning • NUMPY • PANDAS • MATPLOTLIB • SEABORN
- 10. Numpy • Numpy is a python library used for working with arrays. • It has also functions for working in domain of linear algebra, fourier transform and matrices. • In python we have lists that serve the purpose of arrays, but they are slow to process. Numpy aims to provide an array object that is up-to 50x faster than traditional python lists. • Numpy has standard trigonometric functions which return trigonometric ratios.
- 11. Pandas • Pandas is a high level data manipulation tool developed by Wes Mckinney. It is built on the Numpy packages and its key data structure is called the data frame. Data frames allows you to store and manipulate tabular data in rows of observations and columns of variables. • Pandas has been one of the most popular and favorite data science tools used in python programming language for data wrangling and analysis. Data is unavoidably messy in real world. And pandas is seriously a game changer when it comes to cleaning, transforming, manipulating and analyzing data.
- 12. Matplotlib • Matplotlib.pyplot is a collection of functions that make Matplotlib work like MatLab. Each pyplot function makes some change to a figure: e.g., creates a figure, create a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc. • Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in python.
- 13. Seaborn • Seaborn is a library that uses Matplotlib underneath to plot graphs. It will be used to visualize random variables. • The seaborn package was developed based on the Matplotlib library. It is used to create more attractive and informative statistical graphics. While seaborn is a different package, it can also be used to develop the attractiveness of Matplotlib graphics.
- 14. Machine Learning Algorithms • Linear Regression. • Logistic Regression. • Decision tree. • KNN (k-nearest Neighbors) • Random Forest