Introduction -- Data Science and Machine Learning using Python - A Bootcamp | Dr. Junaid Qazi, PhD | Skillshare

Introduction -- Data Science and Machine Learning using Python - A Bootcamp

Dr. Junaid Qazi, PhD, Data Scientist

Introduction -- Data Science and Machine Learning using Python - A Bootcamp

Dr. Junaid Qazi, PhD, Data Scientist

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4 Lessons (10m)
    • 1. Class 0 - Intro - Bootcamp (Class 1 to 10)

      0:11
    • 2. PreFace - Course Contents

      2:16
    • 3. Bootcamp Introduction

      7:00
    • 4. What next in class 1 of 10?

      0:10
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About This Class

Greetings, 

I am so excited to learn that you have started your path to becoming a Data Scientist  with my course. Data Scientist is in-demand and most satisfying career, where you will solve the most interesting problems and challenges in the world. Not only, you will earn average salary of over $100,000 p.a., you will also see the impact of your work around your, is not is amazing?

This is one of the most comprehensive course on any e-learning platform (including Udemy marketplace)which uses the power of Python to learn exploratory data analysis and machine learning algorithms. You will learn the skills to dive deep into the data and present solid conclusions for decision making. 

Data Science bootcamps are costly, in thousands of dollars. However, this course is only a fraction of the cost of any such bootcamp and includes HD lectures along with  detailed code notebooks for every lecture. The course also includes practice exercises on real data for each topic you cover, because the goal is "Learn by Doing"! 

For your satisfaction, I would like to mention few topics that we will be learning in these 10 classes:

  • Basis Python programming for Data Science

  • Data Types, Comparisons Operators, if, else, elif statement, Loops, List Comprehension, Functions, Lambda Expression, Map and Filter

  • NumPy

  • Arrays, built-in methods, array methods and attributes, Indexing, slicing, broadcasting & boolean masking, Arithmetic Operations & Universal Functions

  • Pandas

  • Pandas Data Structures - Series, DataFrame, Hierarchical Indexing, Handling Missing Data, Data Wrangling - Combining, merging, joining, Groupby, Other Useful Methods and Operations, Pandas Built-in Data Visualization

  • Matplotlib

  • Basic Plotting & Object Oriented Approach

  • Seaborn

  • Distribution & Categorical Plots, Axis Grids, Matrix Plots, Regression Plots, Controlling Figure Aesthetics

  • Plotly and Cufflinks

  • Interactive & Geographical plotting

  • SciKit-Learn(one of the world's best machine learning Python library) including:

  • Liner Regression

  • Over fitting , Under fitting Bias Variance Tradeoff

  • Logistic Regression

  • Confusion Matrix, True Negatives/Positives, False Negatives/Positives, Accuracy, Misclassification Rate / Error Rate, Specificity, Precision

  • K Nearest Neighbour

  • Curse of Dimensionality, Model Performance

  • Decision Trees

  • Tree Depth, Splitting at Nodes, Entropy, Information Gain 

  • Random Forest

  • Bootstrap, Bagging (Bootstrap Aggregation)

  • K Mean Clustering

  • Elbow Method 

  • Principle Component Analysis (PCA)

  • Support Vector Machine

  • Recommender Systems

  • Natural Language Processing (NLP)

  • Tokenization, Text Normalization, Vectorization, BoW, TF-IDF, Pipeline feature........and MUCH MORE..........!

Not only the hands-on practice using tens of real data project, theory lectures are also provided to make you understand the working principle behind the Machine Learning models.

So, what are you waiting for, this is your opportunity to learn the real Data Science with a fraction of the cost of any of your undergraduate course.....!

Brief overview of Data around us:

According to IBM, we create 2.5 quintillion bytes of data daily and 90% of the existing data in the world today, has been created in the last two years alone. Social media, transections records, cell phones, GPS, emails, research, medical records and much more…., the data comes from everywhere which has created a big talent gap and the industry, across the globe, is experiencing shortage of experts who can answer and resolve the challenges associated with the data. Professionals are needed in the field of Data Science who are capable of handling and presenting the insights of the data to facilitate decision making. This is the time to get into this field with the knowledge and in-depth skills of data analysis and presentation.

Have Fun and Good Luck! 

Meet Your Teacher

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Dr. Junaid Qazi, PhD

Data Scientist

Teacher

Dr. Qazi has a solid knowledge of Maths, Statistics that are key to Data Science and Machine Learning. He holds MS in Computer Science and PhD degree.  As a mentor and a researcher scientist, with over 17 years of professional experience, Dr. Qazi has developed a skill set in data cleaning/mining, data analysis & data modelling, project management, teaching & training and career advising while working with academic and industrial giants. Dr. Qazi has also served in academia for several years at the rank of lecturer and assistant professor. During his career, he won several funding awards for his research ideas and published high quality articles in well reputed international journals in collaboration with leading scientists from University of British Columbia, Canada; Uni... See full profile

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Transcripts

1. Class 0 - Intro - Bootcamp (Class 1 to 10): 2. PreFace - Course Contents: - Yeah . 3. Bootcamp Introduction : Hi, guys. I'm Jeanette Cosy. As a mentor and research scientist with over 17 years of professional experience, I have developed this skill set in data mining analysis and mortally, while working with economic and industrial giants in Asia, Europe and North America. I have trained hundreds of students in the class. Now I'm here to teach you the most demanding skills in the world today. Which data science and machine learning data science is in demand and most satisfying. Kailua, where you will solve the most interesting problems and challenges in divorce. Not only you will get an opportunity on high salaries. You will also see the impact of your walk around you in the organization and the people you're working with. This course especially designed for you guys. This is one of the most comprehensive course on any e learning platforms which uses the power of python to learn exploratory data analysis and machine learning algorithms. You learned the skins to dive deep into the data and present solid outcomes for decision making. For your knowledge, data science boot camps are costly in thousands of dollars. Heiler this course is only a fraction of the cost and includes over 25 hours of high quality lectures, along with court notebooks, on details for every lecture and plenty exercises on real data set for each topic you will cover. So let's have a quick overview on the topics we're going to cover in this course. Even start with departure Really long Key concepts in part on essential section, we will talk about pythons, data Times comparison operators, if else and if statements, loops, list comprehension functions and Lambda expressions, map and filter and much more and the most important thing practice exercises at the end of the section to improve the skill set and hands on training. After getting hands on training on Parton programming, we'll move on to explore the data analysis capabilities in Piper using It's still off the art libraries Numb pie and turn us. Nope. I is a fundamental package for scientific computing in Pirata, whereas China's is an open source library providing high performance, easy to use data structures and did an analysis tools for python programming language. After getting a seal on data analysis skills, we'll move on to the did a realization section. The realization have significant importance in the field of data signs and fightin provides bit libraries for destabilization. In this section, we will start that Matt for Clip, which is the most popular porting library for Pitre. We will then move on to the Seaborn. It provides a high level interface for drying a collective statistical glass. We will then come back to power Notch. This time, we've been learned did a realization in partners. Panoz comes with its built in did a realization capabilities, which is very handy for quick realization. We will explore a vital variety of plotting options that comes with panels in this section . Drivel then move onto deplorably and Coughlin's for interactive and geographical plotting. You've learned that how easy it is to get interactive parts using these state of the art libraries with solid skills in data analysis and data realization, we will move on towards the Capstone project. This is your opportunity to put a seal on your data analysis and did A realization skips once again you're going to walk with zeal data sets in Capstone products after getting a seal in data analysis and did a realization skills using python. We will move on to the machine learning part machine learning is one of the most important skill in the field of data science. We're going to use the state of the Art Machine Learning Library in Pirata, which is psychic long. We will explore range off machine learning models. In this section, we will talk about linear regression logistic regression can nearest neighbors, which is cayenne decision trees and random forests. Support factor machines came in clustering and principal component analysis. I want to mention that it is very important to know the terry behind immortal aspirin, so each machine learning section will start with detailed theory, lecture and working principle behind the moral. After a theory lecture, we will move on to the Jupiter notebook for hands on training, using real data projects. At the end of each machine learning model, you will practice your skills using additional real data projects, so each model in this machine learning section will involve at least two really later products. Once again, our focus is your training and to provide you the range of carrier options. For this reason, I have added couple off additional topics. In this course, you will learn how the recommended systems walk with Real did a product. We will also explore the nature language processing using another very important library in python, which is N L T K. Once again, using real data sets and hands on training with design is a commander systems and clean our moral using real data in NLP section with every additional topic. It Terry lecture is also provided for you to get a better understanding off the topic. So this was a brief interaction. What are you waiting for now? Join me in this course to become a data scientist, you got an opportunity, the fulfill your dreams and all handsome amount of money. You're going to learn the skills to make the difference in the society using the power after data. This is a job ready course for you. And I'm so excited and looking forward to see you in this course. Join me in this exciting journey, seeing the next lecture where we're going to do the real data science. Good luck 4. What next in class 1 of 10?: