Analyze data quickly and easily with Python's powerful libraries! -- beginners welcome!.
Dr. Haleema
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Rating
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- 251 Students Enrolled
- 04:23 Hours
Course Overview
This course is a complete guide to practical data science using Python. This course covers all the aspects of practical data science and if you take this course alone, you can do away with taking other courses or buying books on Python-based data science.
In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By storing, filtering, managing, and manipulating data in Python, you can give your company a competitive edge & boost your career to the next level!
LIVE COURSE - BATCH STARTING FROM 12th SEPTEMBER 2020
Who this course is for:
- Data analysts and business analysts
- People Looking To Work With Real Life Data In Python
- Anyone Looking To Become Proficient In Exploratory Data Analysis, Statistical Modelling & Visualizations Using Python
What you'll learn
- Understanding the difference between AI, ML and DL, Meaning of Data & Data Science, Types of Data, Types of ML Techniques.
- Importance of Data Preparation in ML, What is EDA and Why EDA, Steps in Understanding Data through EDA.
- What is Data Preprocessing and Why is it needed, Steps in Data Preprocessing.
- Getting our hands dirty with coding.
Course Curriculum
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Introduction 00:02:09
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Introduction 00:02:09
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Data And Types Of Data 00:06:07
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Data And Types Of Data 00:06:07
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What Is Data Science 00:01:50
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What Is Data Science 00:01:50
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What Is AI And ML 00:09:42
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What Is AI And ML 00:09:42
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Difference Between AI ... 00:08:52
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Difference Between AI , ML And DL 00:08:52
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Types Of ML Technique 00:27:23
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Types Of ML Technique 00:27:23
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Need For Data Preparat... 00:29:42
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Need For Data Preparation In ML 00:29:42
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EDA(Term Deposit Sale ... 00:21:05
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Converting Numeric Var... 00:05:31
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Display Statistical Su... 00:03:58
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Display Statistical Summary 00:03:58
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Univariate Analysis 00:32:17
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Univariate Analysis 00:32:17
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Bivariate Analysis 00:17:28
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Bivariate Analysis 00:17:28
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Data Preprocessing 00:10:50
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Data Preprocessing 00:10:50
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Data Preprocessing Par... 00:19:04
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Data Preprocessing Part - 2 00:19:04
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Label Encoding Or One ... 00:20:05
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Label Encoding Or One hot Encoding 00:20:05
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Normalizing Data 00:15:26
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Normalizing Data 00:15:26
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Training set & Tes... 00:09:29
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Training set & Test set 00:09:29
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Creating Ensemble mode... 00:22:37
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Creating Ensemble model 00:22:37
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This Course Include:
- 04:23 Hours On-Demand Videos
- 18 Lessons
- Lifetime Access
- Access on Mobile and TV
- Certificate of Completion