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Welcome to our hands-on video course, where you will learn technologies, such as React, Redux Toolkit, Express, and MongoDB. You will learn how to structure your code using Redux Toolkit, implement powerful features with React, and create a robust backend using Express and MongoDB. An understanding of modern JS fundamentals and the basics of React will be an add-on.

Overview This comprehensive course on Statistics & Probability for Data Science & Machine Learning will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Statistics & Probability for Data Science & Machine Learning comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Statistics & Probability for Data Science & Machine Learning. It is available to all students, of all academic backgrounds. Requirements Our Statistics & Probability for Data Science & Machine Learning is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 10 sections • 89 lectures • 11:27:00 total length •Welcome!: 00:02:00 •What will you learn in this course?: 00:06:00 •How can you get the most out of it?: 00:06:00 •Intro: 00:03:00 •Mean: 00:06:00 •Median: 00:05:00 •Mode: 00:04:00 •Mean or Median?: 00:08:00 •Skewness: 00:08:00 •Practice: Skewness: 00:01:00 •Solution: Skewness: 00:03:00 •Range & IQR: 00:10:00 •Sample vs. Population: 00:05:00 •Variance & Standard deviation: 00:11:00 •Impact of Scaling & Shifting: 00:19:00 •Statistical moments: 00:06:00 •What is a distribution?: 00:10:00 •Normal distribution: 00:09:00 •Z-Scores: 00:13:00 •Practice: Normal distribution: 00:04:00 •Solution: Normal distribution: 00:07:00 •Intro: 00:01:00 •Probability Basics: 00:10:00 •Calculating simple Probabilities: 00:05:00 •Practice: Simple Probabilities: 00:01:00 •Quick solution: Simple Probabilities: 00:01:00 •Detailed solution: Simple Probabilities: 00:06:00 •Rule of addition: 00:13:00 •Practice: Rule of addition: 00:02:00 •Quick solution: Rule of addition: 00:01:00 •Detailed solution: Rule of addition: 00:07:00 •Rule of multiplication: 00:11:00 •Practice: Rule of multiplication: 00:01:00 •Solution: Rule of multiplication: 00:03:00 •Bayes Theorem: 00:10:00 •Bayes Theorem - Practical example: 00:07:00 •Expected value: 00:11:00 •Practice: Expected value: 00:01:00 •Solution: Expected value: 00:03:00 •Law of Large Numbers: 00:08:00 •Central Limit Theorem - Theory: 00:10:00 •Central Limit Theorem - Intuition: 00:08:00 •Central Limit Theorem - Challenge: 00:11:00 •Central Limit Theorem - Exercise: 00:02:00 •Central Limit Theorem - Solution: 00:14:00 •Binomial distribution: 00:16:00 •Poisson distribution: 00:17:00 •Real life problems: 00:15:00 •Intro: 00:01:00 •What is a hypothesis?: 00:19:00 •Significance level and p-value: 00:06:00 •Type I and Type II errors: 00:05:00 •Confidence intervals and margin of error: 00:15:00 •Excursion: Calculating sample size & power: 00:11:00 •Performing the hypothesis test: 00:20:00 •Practice: Hypothesis test: 00:01:00 •Solution: Hypothesis test: 00:06:00 •T-test and t-distribution: 00:13:00 •Proportion testing: 00:10:00 •Important p-z pairs: 00:08:00 •Intro: 00:02:00 •Linear Regression: 00:11:00 •Correlation coefficient: 00:10:00 •Practice: Correlation: 00:02:00 •Solution: Correlation: 00:08:00 •Practice: Linear Regression: 00:01:00 •Solution: Linear Regression: 00:07:00 •Residual, MSE & MAE: 00:08:00 •Practice: MSE & MAE: 00:01:00 •Solution: MSE & MAE: 00:03:00 •Coefficient of determination: 00:12:00 •Root Mean Square Error: 00:06:00 •Practice: RMSE: 00:01:00 •Solution: RMSE: 00:02:00 •Multiple Linear Regression: 00:16:00 •Overfitting: 00:05:00 •Polynomial Regression: 00:13:00 •Logistic Regression: 00:09:00 •Decision Trees: 00:21:00 •Regression Trees: 00:14:00 •Random Forests: 00:13:00 •Dealing with missing data: 00:10:00 •ANOVA - Basics & Assumptions: 00:06:00 •One-way ANOVA: 00:12:00 •F-Distribution: 00:10:00 •Two-way ANOVA - Sum of Squares: 00:16:00 •Two-way ANOVA - F-ratio & conclusions: 00:11:00 •Wrap up: 00:01:00 •Assignment - Statistics & Probability for Data Science & Machine Learning: 00:00:00

Overview This comprehensive course on Python for Data Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python for Data Analysis comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is this course for? There is no experience or previous qualifications required for enrolment on this Python for Data Analysis. It is available to all students, of all academic backgrounds. Requirements Our Python for Data Analysis is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 19 sections • 99 lectures • 00:08:00 total length •Welcome & Course Overview: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:37:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method ..: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00 •Resources- Python for Data Analysis: 00:00:00

This course will help you to gain a mastery level understanding of the fundamentals of Android Studio, Android app development, and the Kotlin programming language by building six full-fledged applications as well as many more 'learning' applications throughout the course.

How good you are at solving problems defines your leadership. If you can solve a problem with logical reasoning and critical thinking you will be considered an expert in your industry. Critical Thinking Training will teach you essential methods and strategies to process information to solve difficult problems. In this course, you will develop problem-solving skills, logical thinking skills and rational thinking skills that will make you a true leader in your industry. Enrol in this course today, and boost your career in a leadership role. Key Topics: Components of critical thinking explained What is non-linear thinking? How to change perspective Benefits of critical thinking How to evaluate the information How to solve any problem This Critical Thinking Training Course is the only guide you need for learning the essential topics thoroughly and acquiring the necessary skills for a special discounted price. With only 1 hour of training towards your CPD Accredited Certificate and course materials designed by industry experts, any of your dreams in professional life can be turned into a reality. Our exclusive training follows an advanced curriculum with topics broken down into a total of 10 scaled-down modules for your ease of self-paced learning. These modules will assist you in grasping the basics and leading you to the steps of getting a comprehensive understanding of all aspects of training. The course materials designed by experts are easily accessible 24/7 by any of your smartphones, laptops, PCs, tablets etc. Our expert instructors are available on weekdays to listen to any of your queries via email and help you in achieving your goals. You'll get a Free Student ID card by enrolling in this training course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards. Enrolling on the course will ensure that you land your dream career faster than you thought possible. Stand out from the crowd and train for the job you want with the program. Learning Outcomes of Critical Thinking Training: Understand the components Know how to utilise non-linear thinking in real life Learn how to evaluate information using these skills Gain comprehend problem-solving abilities Learn how to revise perspective, when necessary Understand how to use logical thinking in real life Experts created the Critical Thinking Training course to provide a rich and in-depth training experience for all students who enrol in it. Enrol in the course right now and you'll have immediate access to all of the course materials. Then, from any internet-enabled device, access the course materials and learn when it's convenient for you. Start your learning journey straight away with this course and take a step toward a brighter future! Skills You Will Gain Excellent problem-solving abilities Ability to use logical thinking in real life Critical thinking skills Ability to utilize non-linear thinking in real life Ability to evaluate information using skills Why should you choose the course with Academy for Health & Fitness? Opportunity to earn a certificate accredited by CPD after completing this course Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery) Globally accepted standard structured lesson planning Innovative and engaging content and activities Assessments that measure higher-level thinking and skills Complete the program in your own time, at your own pace Each of our students gets full 24/7 tutor support **** Course Curriculum: **** Here is the curriculum breakdown of the course: Critical Thinking Training Course Module 01: Components Applying Reason Open Mindedness Analysis Logic Module 02: Non-Linear Thinking Step Out of Your Comfort Zone Don't Jump to Conclusions Expect and Initiate Change Being Ready to Adapt Module 03: Logical Thinking Ask the Right Questions Organize the Data Evaluate the Information Draw Conclusions Module 04: Critical Thinkers (I) Active Listening Be Curious Be Disciplined Be Humble Module 05: Critical Thinking (II) Seeing the Big Picture Objectivity Using Your Emotions Being Self-Aware Module 06: Evaluate the Information Making Assumptions Watch out for the Bias Ask Clarifying Questions SWOT Analysis Module 07: Benefits Being More Persuasive Better Communication Better Problem Solving Increased Emotional Intelligence Module 08: Changing Your Perspective Limitations of Your Point of View Considering Others Viewpoint Influences on Bias When New Information Arrives Module 09: Problem Solving Identify Inconsistencies Trust Your Instincts Asking Why? Evaluate the Solution(s) Module 10: Putting It All Together Retaining Your New Skills Reflect and Learn From Mistakes Always Ask Questions Practicing Critical Thinking Assessment Process Once you have completed all the modules in the course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Is This Critical Thinking Training Course Right for You? Anyone interested in learning more about this subject should take this course. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. All are welcome to take this course. There are no prerequisites for enrolment, and you can access the course materials from any location in the world. Requirements The Critical Thinking Training program does not require any prior knowledge; everyone may participate! This course is open to anyone interested in learning from anywhere in the world. Every student must be over the age of 16 and have a passion for learning and literacy. This 100% online course can be accessed from any internet-connected device, such as a computer, tablet, or smartphone. This course allows you to study at your speed and grow a quality skillset. Career path After completing this Critical Thinking Training Course, you are to start your career or begin the next phase of your career in this field. Our entire course will help you to gain a position of respect and dignity over your competitors. The certificate enhances your CV and helps you find work in the field concerned. Certificates CPD Accredited Certificate Digital certificate - £10 CPD Accredited Certificate Hard copy certificate - £29 If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.

Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents, and interests with our special Advanced Mathematics Training Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides the professional training that employers are looking for in today's workplaces. The Advanced Mathematics Training Course is one of the most prestigious training offered at Skillwise and is highly valued by employers for good reason. This Advanced Mathematics Training Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Advanced Mathematics Training Course, like every one of Skillwise's courses, is meticulously developed and well-researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At Skillwise, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from Skillwise, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Advanced Mathematics Training ? Lifetime access to the course forever Digital Certificate, Transcript, and student ID are all included in the price Absolutely no hidden fees Directly receive CPD Quality Standard-accredited qualifications after course completion Receive one-to-one assistance every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Advanced Mathematics Training there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the PDF certificate for free. Original Hard Copy certificates need to be ordered at an additional cost of £8. Who is this course for? This Advanced Mathematics Training course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already work in relevant fields and want to polish their knowledge and skills. Prerequisites This Advanced Mathematics Training does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Advanced Mathematics Training was made by professionals and it is compatible with all PCs, Macs, tablets, and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as a bonus, you will be able to pursue multiple occupations. This Advanced Mathematics Training is a great way for you to gain multiple skills from the comfort of your home. Introduction Introduction 00:01:00 Mathematical Logic Introduction to Mathematical Logic, What is Sentence,Statements and their Types 00:02:00 Intro to Logical Connectivity,Tautology,Contradiction,Contingency,Pattern 00:06:00 Quantitative and Quantified Statement and types and example 00:03:00 Dual : Replacing of Connections and Symbols 00:02:00 Negations of Compound Statement , Converse, Inverse , & Contrapositive 00:03:00 Algebra of Statements and Law 00:05:00 Real Life application of Logic to Switching Electric Circuit 00:05:00 Matrices Intro to Matrices , Multiplication and Addition using Matrix 00:06:00 Inverse of Matrix Uniqueness of Inverse,Elementary Transformation 00:08:00 Method of REDUCTION AND INVERSION with real life example how we can implement 00:17:00 Trigonometric Functions Introduction to Trigonometric Function 00:03:00 General Solutions And Theorem 00:10:00 Solution of Triangle : Polar Co-ordinates 00:21:00 Rules and Theorems of SIn Cosine and TAN 00:22:00 Inverse Trigonometric Function 00:25:00 Pair Of Straight Line Introduction & Combined Equations 00:07:00 Degrees and Types 00:12:00 Some Theorem 00:17:00 Lines & Planes Introduction - vector cartesian theorem 00:02:00 Cartesian Equation & 2 Point Theorem 00:03:00 Theorems & Problem Solving 00:05:00 Distance of Point Line 00:05:00 Skew Lines 00:01:00 Distance of skew lines 00:03:00 Distance between parallel lines 00:02:00 Equation of Plane and Cartesian Form 00:10:00 Linear Programming Linear Programming Introduction 00:08:00 Introduction to LPP (Linear Programming Problem) 00:05:00 LPP PROBLEM SOLVING 00:07:00 Order Your Certificate Order Your Certificate QLS

This course equips learners with a comprehensive understanding of the NumPy stack, including NumPy, Matplotlib, Pandas, and SciPy, to effectively tackle common challenges in deep learning and data science. Master the basics with this carefully structured course.

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Overview In this age of technology, data science and machine learning skills have become highly demanding skill sets. In the UK a skilled data scientist can earn around £62,000 per year. If you are aspiring for a career in the IT industry, secure these skills before you start your journey. The Complete Machine Learning & Data Science Bootcamp 2023 course can help you out. This course will introduce you to the essentials of Python. From the highly informative modules, you will learn about NumPy, Pandas and matplotlib. The course will help you grasp the skills required for using python for data analysis and visualisation. After that, you will receive step-by-step guidance on Python for machine learning. The course will then focus on the concepts of Natural Language Processing.  Upon successful completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. So enrol today! How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? Anyone with an interest in learning about data science can enrol in this course. It will help aspiring professionals develop the basic skills to build a promising career. Professionals already working in this can take the course to improve their skill sets. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush.   Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst Course Curriculum 18 sections • 98 lectures • 23:48:00 total length •Welcome & Course Overview6: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:17:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method.: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00

Get started with Neural networks and understand the underlying concepts of Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks. This hands-on course will help you understand deep learning in detail with no prior coding or programming experience required.