Course curriculum
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1
Welcome to the course!
- About this course: Overview, Learning Outcomes, Who Should Enroll...
- Instructor bio - Pramod Gupta
- Course content noted as "Pending" will be published after it streams live, on air
- Key pointers for this program
- Joining the Alumni Community
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2
Module 1
- Module 1 - Introduction to Python, Libraries and Installation
- Module 1 - SLIDES
- Segment - 01 - Introduction
- Segment - 02 - A bit about artificial intelligence and machine learning
- Segment - 03 - Software choices for AI and ML
- Segment - 04 - Data Mining process
- Segment - 05 - What is data and data analysis?
- Segment - 06 - Data quality and its measure
- Segment - 07 - Data analysis
- Segment - 08 - Installing Python, Running Juypter Notebook
- Segment - 09 - Data analytics philosophy and teaching
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3
Module 2
- Module 2 - Data Structures in Python, Lists and Tuples and Various Operations
- Segment - 10 - Python Basics
- Segment - 11 - Strings
- Segment - 12 - Other Functions and Help
- Segment - 13 - Data Structures and Lists
- Segment - 14 - List Comprehension
- Segment - 15 - Tuple Data Structure
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4
Module 3
- Module 3 - Data Structures in Python, Dictionaries and Sets and Various Operations
- Segment - 16 - Dictionary and Data Structures
- Segment - 17 - Sets
- Segment - 18 - Set Comprehension and Control Flow
- Segment - 19 - NumPy and-SciPy
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5
Module 4
- Module 4 - Introduction to NumPy, 1D Array and 2D Arrays
- Segment - 20 - NumPy in Depth
- Segment - 21 - Indexing
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6
Module 5
- Module 5 - Deep Dive into NumPy and Various Operations with Arrays
- Segment - 22 - Array Operations and Mathematics
- Segment - 23 - Sorting Arrays
- Segment - 24 - Broadcasting
- Segment - 25 - Dot Matrices
- Segment - 26 - logical-operations
- Segment - 27 - Saving NumPy to CSV Files
- Segment - 28 - Introduction to Pandas
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7
Module 6
- Module 6 - Introduction to Pandas, Pandas Series and Various Operations on Series
- Segment - 29 - Pandas
- Segment - 30 - Pandas Series
- Segment - 31 - operations-on-series
- Segment - 32 - Arithmetic Operations
- Segment - 33 - Sorting
- Segment - 34 - Data Cleaning
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8
Module 7
- Module 7 - Intro to Pandas DataFrame and Various Operations with DataFrames
- Segment - 35 - Dataframes
- Segment - 36 - Further Dataframe Operations
- Segment - 37 - Still More Dataframe Operations
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9
Module 8
- Module 8 - Data Cleaning and Transformation with Pandas
- Segment - 38 - Data Cleaning and Transformation
- Segment - 39 - Manor Tasks in Data Transformation
- Segment - 40 - DataFrames and Transforming Data
- Segment - 41 - Dealing with Missing Data
- Segment - 42 - Discretization and Binning
- Segment - 43 - Detecting and Filtering Outliers
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10
Module 9
- Module 9 - Data Visualization with Matplotlib/Seaborn
- Segment - 44 - Data Visualization Foundations
- Segment - 45 - Basic Data Visualization Principles
- Segment - 46 - Selecting the Right Chart Type and Tools
- Segment - 47 - Types and Uses of Graphs
- Segment - 48 - Matplotlib
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11
Module 10
- Module 10 - Introduction to Machine Learning and Scikit-Learn
- Segment - 49 - The Basics of Machine Learning
- Segment - 50 - Steps to Applying Machine Learning
- Segment - 51 - Machine Learning Paradigms
- Segment - 52 - Why Machine Learning and Why Now
- Segment - 53 - Measuring Model Performance
- Segment - 54 - Scikit-Learn Introduction
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12
Labs
- Labs - Overview
- Instructions: Using Jupyter Notebooks
- Instructions: Virtual labs (For Colaboratory)
- Labs: Module 1
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13
Quizzes
- Quiz - Overview
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14
Additional Course Readings
- Articles and downloads
- Best books on this subject
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15
Final Exam
- Final Exam: Overview and Instructions
- Final Exam: Launch here
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16
Recommended Further Readings
- Articles and Downloads
- Best books on this subject