Complete Business Intelligence (BI) With Python Bootcamp
Complete Business Intelligence (BI) With Python Bootcamp, available at $44.99, has an average rating of 4.5, with 64 lectures, based on 51 reviews, and has 363 subscribers.
You will learn about Learn the main aspects of implementing a Python data science framework within Google Colab Learn to obtain both unstructured and structured data from different sources including Twitter, SQL databases and freely available financial data Create powerful data visualisations to both understand your data and present your findings Implemented unsupervised learning algorithms to obtain insights from real-life business and financial datasets such as those related to stock market performan Implement common statistical techniques to extract valuable insights and answer questions Implement powerful machine learning algorithms to build predictive and forecasting models Use common natural language processing (NLP) techniques to learn what your customers are really saying in their Amazon reviews This course is ideal for individuals who are People Wanting To Master The Python/Google Colab Environment For Data Science or People Interested in Applying Python Data Science Techniques For BI Problems or Students Interested In Developing Powerful Data Visualisations or Students Wanting To Derive Business Relevant Insights From Structured and Unstructured Data It is particularly useful for People Wanting To Master The Python/Google Colab Environment For Data Science or People Interested in Applying Python Data Science Techniques For BI Problems or Students Interested In Developing Powerful Data Visualisations or Students Wanting To Derive Business Relevant Insights From Structured and Unstructured Data.
Enroll now: Complete Business Intelligence (BI) With Python Bootcamp
Summary
Title: Complete Business Intelligence (BI) With Python Bootcamp
Price: $44.99
Average Rating: 4.5
Number of Lectures: 64
Number of Published Lectures: 64
Number of Curriculum Items: 64
Number of Published Curriculum Objects: 64
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn the main aspects of implementing a Python data science framework within Google Colab
- Learn to obtain both unstructured and structured data from different sources including Twitter, SQL databases and freely available financial data
- Create powerful data visualisations to both understand your data and present your findings
- Implemented unsupervised learning algorithms to obtain insights from real-life business and financial datasets such as those related to stock market performan
- Implement common statistical techniques to extract valuable insights and answer questions
- Implement powerful machine learning algorithms to build predictive and forecasting models
- Use common natural language processing (NLP) techniques to learn what your customers are really saying in their Amazon reviews
Who Should Attend
- People Wanting To Master The Python/Google Colab Environment For Data Science
- People Interested in Applying Python Data Science Techniques For BI Problems
- Students Interested In Developing Powerful Data Visualisations
- Students Wanting To Derive Business Relevant Insights From Structured and Unstructured Data
Target Audiences
- People Wanting To Master The Python/Google Colab Environment For Data Science
- People Interested in Applying Python Data Science Techniques For BI Problems
- Students Interested In Developing Powerful Data Visualisations
- Students Wanting To Derive Business Relevant Insights From Structured and Unstructured Data
ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT CARRYING OUT BUSINESS INTELLIGENCE WITH PYTHON
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Are you interested in harnessing the power of structured and unstructured data for informing business decisions?
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Do you want to make data-driven financial decisions?
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Do you want to turn unstructured data from social media posts, articles and web pages into real insights?
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Do you want to develop cutting edge analytics and visualisations to support business decisions?
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Are you interested in deploying predictive modelling and forecasting methods to get an edge over the competition?
You Can Gain An Edge Over Other Data Scientists If You Can Apply Python Data Analysis Skills For Practical Business Intelligence (BI)
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By enhancing the value of your company or business through the extraction of actionable insights from commonly used structured and unstructured business data
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Stand out from a pool of other data analysts by gaining proficiency in the most important pillars of BI applications
MY COURSE IS A HANDS-ON TRAINING WITH REAL BUSINESS RELATED PROBLEMS- You will learn to use important Python data science techniques to derive information and insights from both structured data (such as those obtained from databases) and unstructured text data
My course provides a foundation to carry out PRACTICAL, real-life BI tasks using Python. By taking this course, you are taking an important step forward in your data science journey to become an expert in deploying Python data science techniques for answering practical business questions (e.g. what kind of customers sign up for a long-term phone plan?).
Why Should You Take My Course?
I have an MPhil (Geography and Environment) from the University of Oxford, UK. I also completed a data science intense PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real-life data from different sources and producing publications for international peer-reviewed journals.
This course will help you gain fluency in deploying data science-based BI solutions using a powerful clouded based python environment called GoogleColab. Specifically, you will
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Learn the main aspects of implementing a Python data science framework within Google Colab
-
Learn to obtain both unstructured and structured data from different sources including Twitter, SQL databases and freely available financial data
-
Implemented unsupervised learning algorithms to obtain insights from real-life business and financial datasets such as those related to stock market performance
-
Implement common statistical techniques to extract valuable insights and answer questions such as which customers are likely to sign up for a long-term phone plan or how do Airbnb rentals vary across the different cities in Australia.
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Implement powerful machine learning algorithms to build predictive and forecasting models
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Carry out common analytics and visualization tasks
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Use common natural language processing (NLP) techniques to learn what your customers are really saying in their Amazon reviews
You will work on practical mini case studies relating to (a) Airbnb rentals in Australia (b) stock price data relating to the major companies listed on the Nasdaq (c) phone company customer turn over (d) textual data of Amazon reviews
In addition to all the above, you’ll have MY CONTINUOUS SUPPORT to make sure you get the most value out of your investment!
ENROLL NOW 🙂
Course Curriculum
Chapter 1: Welcome to the Course
Lecture 1: Welcome Top the Course
Lecture 2: Data and Code
Lecture 3: Python Installation
Lecture 4: Different Data Types
Lecture 5: Start With Google Colaboratory Environment
Lecture 6: Google Colabs and GPU
Chapter 2: Basics Of Python For Data Science
Lecture 1: Introduction to Pandas
Lecture 2: Read In Multiple CSVs
Lecture 3: Python Data Cleaning
Lecture 4: Assess Data Quality
Lecture 5: Retain Columns With No NA Values
Lecture 6: Dealing With Missing Values
Lecture 7: Read In Data From SQL
Chapter 3: Obtaining Financial Data
Lecture 1: Obtain Stock Prices
Lecture 2: Use Quandl-Part 1
Lecture 3: Use Quandl-Part 2
Lecture 4: Obtain Financial Data From Yahoo
Lecture 5: Obtaining Financial Data
Lecture 6: Compute Technical Indicators- Simple Moving Average (SMA)
Chapter 4: Acquiring data Via APIs and Social Media
Lecture 1: The Importance of Unstructured Data
Lecture 2: What Are APIs?
Lecture 3: Introduction To The Foursquare API
Lecture 4: Obtaining Text Data From Reddit
Lecture 5: Obtain Twitter Data Sans API
Lecture 6: Get The News Headlines of the Day
Lecture 7: News Headlines From Google News
Lecture 8: Financial News Headlines
Lecture 9: Gaining Insights From Amazon Reviews
Chapter 5: Data Visualisation For Business Intelligence
Lecture 1: What Are Data Visualisations?
Lecture 2: Theoretical Principles Behind Data Visualisations
Lecture 3: Histograms
Lecture 4: Line chart
Lecture 5: Multiline
Chapter 6: Inferential Statistics For Business Intelligence
Lecture 1: Theory Behind Correlation Analysis
Lecture 2: Stock Market Price Correlations
Lecture 3: Visualise Customer Churn: Crosstabulation
Lecture 4: More Crosstabulation
Lecture 5: Theory Behind Principal Component Analysis (PCA)
Lecture 6: PCA From First Principles
Lecture 7: Implement PCA- The Usual Way
Lecture 8: Multiple Correspondence Analysis (MCA)
Lecture 9: Principal Components When You Have Both Categorical and Quantitative Variables
Lecture 10: Components of Time Series
Lecture 11: Why Forecast: An Example
Lecture 12: Forecasting
Lecture 13: How Do your Sales Vary-Part1
Lecture 14: How Do Your Sales Vary-Part2
Chapter 7: Machine Learning
Lecture 1: Welcome To Generalised Linear Modelling (GLM)
Lecture 2: Logistic Regression-Binary Outcomes
Lecture 3: Logistic Regression-Part 2
Lecture 4: Logistic Regression: A Statistical Perspective
Lecture 5: Accuracy Assessments (Binary Classifications)
Lecture 6: What is Machine Learning (ML)?
Lecture 7: Unsupervised Learning Theory
Lecture 8: k-Means Theory
Lecture 9: Cluster Your Stocks
Lecture 10: Hierarchical Clustering-Quick Intuition
Lecture 11: Hierarchical Clustering Of Stocks
Lecture 12: Supervised Learning Theory
Lecture 13: Random Forest (RF) Theory
Lecture 14: Fit an RF Regression Model
Lecture 15: Evaluate the RF Regression Model
Chapter 8: Miscellaneous Information
Lecture 1: Introduction to Dictionaries
Lecture 2: What Is Numpy?
Instructors
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Minerva Singh
Bestselling Instructor & Data Scientist(Cambridge Uni)
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 1 votes
- 3 stars: 2 votes
- 4 stars: 12 votes
- 5 stars: 34 votes
Frequently Asked Questions
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Can I take my courses with me wherever I go?
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