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Free Download Udemy - Data Science Mastery - Journey into Machine Learning Last updated: 4/2025 Created by: Tech Career World MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English + subtitle | Duration: 530 Lectures ( 49h 5m ) | Size: 15.6 GB Learn Machine Learning, Data Science and Deep Learning with Python What you'll learn Gain proficiency in using Python libraries commonly used in data science and machine learning, such as NumPy, Pandas, and Matplotlib. Learn how to clean and preprocess datasets, including handling missing data, outliers, and feature scaling. Acquire knowledge of exploratory data analysis techniques to extract insights and patterns from data. Master the fundamentals of statistical analysis and apply statistical methods to interpret and draw conclusions from data. Understand the principles of machine learning and its various algorithms, such as regression, classification, and clustering. Learn how to select appropriate machine learning models and techniques for different types of problems and datasets. Develop skills in feature engineering and selection to enhance the performance of machine learning models. Requirements Just passion for learning! Description The Python for Data Science and Machine Learning course is designed to equip learners with a comprehensive understanding of Python programming, data science techniques, and machine learning algorithms. Whether you are a beginner looking to enter the field or a seasoned professional seeking to expand your skillset, this course provides the knowledge and practical experience necessary to excel in the rapidly growing field of data science.Course Objectives:1. Master Python Programming: Develop a strong foundation in Python programming, including syntax, data structures, control flow, and functions. 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We will show you how to do that step by step work on projects A Willingness to Learn & Practice - Data Science & Machine Learning require hands-on practice, so be ready to experiment and build real-world projects No prior experience in data science or machine learning is needed-I will guide you step by step from the basics to advanced topics Description Course Description Data Science & ML Bootcamp 2025: Real Projects - Go from Beginner to Job-Ready with Hands-On Training! Want to break into high-paying Data Science & Machine Learning roles? This project-based bootcamp gives you the exact skills companies want-no fluff, just real-world training that gets you hired faster!Are you ready to master Data Science & Machine Learning and land a high-paying job in 2025? This comprehensive, project-based course will take you from beginner to expert, giving you the skills needed to work as a Data Scientist, Machine Learning Engineer, or AI Specialist. 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Free Download Udemy - Data Science Zero to Hero by Aman Kumar Published: 3/2025 Created by: Aman Kumar MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English | Duration: 43 Lectures ( 9h 46m ) | Size: 3.7 GB Data Science Zero to Hero: The Complete Bootcamp What you'll learn Develop Proficiency in Python for Data Analysis Apply Statistical Concepts and Techniques for Data Interpretation Build and Evaluate Machine Learning Models Deploy Machine Learning Models and Prepare for Data Science Careers Requirements No prior experience required just a computer with internet access and willingness to Learn Description Are you ready to embark on a transformative journey into the world of Data Science? 'Data Science Zero to Hero: The Complete Bootcamp' is your all-in-one guide to mastering the core concepts and practical skills needed to become a successful Data Scientist. This course takes you from the very basics to advanced techniques, ensuring you gain a solid foundation and hands-on experience.We'll begin with an introduction to Data Science, exploring 'The Data Story' and understanding why 'Data is the new oil.' You'll discover the role of a Data Scientist, and the essential skillsets required. Then, we dive into Python programming, the cornerstone of Data Science. You'll learn everything from Python basics to data manipulation and analysis.Next, we'll delve into Statistics, a crucial component of Data Science. You'll grasp key concepts like percentiles, boxplots, normal distribution, hypothesis testing, and linear equations. We'll then move on to SQL, mastering data management and querying.The heart of the course lies in Machine Learning, where you'll learn and implement algorithms like Linear Regression, Logistic Regression, Decision Trees, Ensemble Models, and Clustering. You'll work on real-world projects to build and deploy these models. Finally, we'll cover Model Deployment and Interview Preparation, equipping you with the tools to launch your Data Science career.This course is designed for anyone eager to learn Data Science, regardless of their prior experience. Whether you're a beginner or looking to enhance your skills, this bootcamp will guide you step-by-step. Enroll today and start your journey to becoming a Data Science hero! Who this course is for Absolute Beginners Career Switchers Students and Recent Graduates Aspiring Data Analysts and Scientists Entrepreneurs and Business Professionals Anyone Curious About Data Homepage: https://www.udemy.com/course/data-science-zero-to-hero/ [b]AusFile[/b] https://ausfile.com/cqyt4a6wh0cs/lrieb.Data.Science.Zero.to.Hero.part1.rar.html https://ausfile.com/6xwk5gjt0ghv/lrieb.Data.Science.Zero.to.Hero.part2.rar.html https://ausfile.com/qharm32qhug5/lrieb.Data.Science.Zero.to.Hero.part3.rar.html https://ausfile.com/4s7eop7gqakk/lrieb.Data.Science.Zero.to.Hero.part4.rar.html Rapidgator https://rg.to/file/7320f441f122ac78fe2892ba484aceba/lrieb.Data.Science.Zero.to.Hero.part1.rar.html https://rg.to/file/dfd7a0f9b5670f6314aa9ccec872121b/lrieb.Data.Science.Zero.to.Hero.part2.rar.html https://rg.to/file/2b5b6d2f8d69b9633697d2cacd35690d/lrieb.Data.Science.Zero.to.Hero.part3.rar.html https://rg.to/file/fc4c562b06be2345fb16e971267e2f28/lrieb.Data.Science.Zero.to.Hero.part4.rar.html Fikper Free Download https://fikper.com/92bG04HwCA/lrieb.Data.Science.Zero.to.Hero.part1.rar.html https://fikper.com/25uYnyewqn/lrieb.Data.Science.Zero.to.Hero.part2.rar.html https://fikper.com/dj8qdarAOr/lrieb.Data.Science.Zero.to.Hero.part3.rar.html https://fikper.com/zWmm8Qa4bX/lrieb.Data.Science.Zero.to.Hero.part4.rar.html No Password - Links are Interchangeable

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Free Download Udemy - SAP Data Science & ML for SAP Consultants Last updated: 1/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 13.42 GB | Duration: 26h 24m Master ML and Data Science on SAP Data: Ultimate Hands-On Techniques for Insightful Analysis What you'll learn Course Provides the Entire Toolbox you need to apply Data Science - Machine Learning Algorithms for your SAP Data Get ahead of crowd by knowing the hottest skill in the current Market Start coding in Python and learn how to use it for Statistical Analysis of SAP Data Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn - Essential tools for Performing Data Science with SAP Data Carry out cluster and factor analysis on SAP Data Learn to Extract the Required Data from SAP System to perform Statistical Analysis & Apply various Machine Learning Models Learn how to pre-process the extracted data from SAP Apply the Skills to real-life business cases Be Industry Ready to apply everything you have learnt to more and more real-life scenarios in the ocean of SAP Build Recommendation Engine Using SAP Data Create a Project Implementation to Perform the Predictive Analytics on SAP Data & Perform the Advanced Time Series Analysis using ARIMA Model Learn to use Advanced Techniques, and make use of Pre-trained Model from Google Cloud Natural Language Processing API for Text Data Requirements No Prior Experience is required. We start from the very basics You will need to install Anaconda. We will show you how to do that - Step by Step Basic Familiarity with SAP Interface (Optional) Description Unlock a New Era in Your Career: Data Science with SAP - Machine Learning for Enterprise DataWelcome to a transformative learning journey designed to bridge the gap between SAP Professionals and Data Scientists. As you embark on this course, you'll discover the striking similarities between the activities performed by Data Scientists and the way SAP Professionals implement business Requirements on ERP Software - SAP. The pivotal distinction lies in the Data Scientists' knack for posing more insightful questions about the data they encounter.Our curriculum, meticulously crafted for SAP Professionals venturing into the realm of Data Science, covers a diverse range of essential topics:Understanding the Data Science Field and Types of Analysis:Gain insights into the fundamental principles and practices of the data science field.Explore various types of analysis that form the backbone of effective data-driven decision-making.Statistics:Delve into statistical concepts, empowering you to make informed decisions based on data-driven insights.Python:Acquire proficiency in Python, a versatile programming language extensively used in the data science landscape.Advanced Statistical Techniques in Python:Apply sophisticated statistical techniques using Python, enhancing your analytical capabilities.Data Visualization:Master the art of visualizing data to convey meaningful insights through compelling graphics.Machine Learning:Dive into the dynamic world of machine learning, understanding its principles and applications.Using Pretrained Models:Leverage the power of pretrained models, including the Google Cloud Natural Language Processing API, for a seamless jumpstart in SAP Application implementation.Each topic seamlessly builds upon the previous ones, providing a structured and comprehensive learning path. 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Free Download Udemy - Data Science Methodology Last updated: 6/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.07 GB | Duration: 2h 36m Understand steps and tasks needed for designing and building a Data Driven AI engagement What you'll learn Learn to articulate data science process and methodology steps Understand how to analyze data sources Create and validate data science models by applying analytics techniques Explore how users and experts will be engaged for model measurement and monitoring Learn how to apply the methodology on a practice problem Requirements This is an introductory course. There are no pre-requisites. Description Data Science grew through our experiences with Business Intelligence or BI, a field that became popular in 1990s. However, the last 20 years have seen unprecedented improvement in our ability to take actions using Artificial Intelligence. As we adopt the BI methodologies to AI deployments, how will these methodologies morph to add considerations needed for model deployment, and machine learning.Today's Data Science work deals with big data. It introduces three major challenges:How to deal with large volumes of data. Data understanding and data preparation must deal with large scale observations about the population. In the world of BI on small samples, the art of data science was to find averages and trends using a sample and then projecting it using universal population measures such as census to project to the overall population. Most of the big data provides significant samples where such a projection may not be needed. However, bias and outliers become the real issuesData is now available in high velocity. Using scoring engines, we can embed insights into high velocity. Data Science techniques offer significant real-time analytics techniques to make it possible. As you interact with a web site or a product, the marketer or services teams can provide help to you as a user. This is due to insight embedded in high velocity.Most of the data is in speech, unstructured text or videos. This is high variety. How do we interpret an image of a driver license and extract driver license. Understanding and interpreting such data is now a central part of data science.As these deployed models ingest learning in real-time and adjust their models, it is important to monitor their performance for biases and inaccuracies. We need measurement and monitoring that is no longer project-based one-time activity. It is continuous, automated, and closely monitored. 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Free Download Udemy - Research Methods in Social Science (Certificate) Published: 3/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 3h 51m | Size: 2.83 GB College level research informational content course used in psychology and the social sciences. What you'll learn Recognize the various types of research methods; Identify ethical concerns within the research process; Describe and develop research questions, frameworks, and study designs; Compare and contrast experimental and nonexperimental research; Recognize the various ways researchers describe data; Identify the key parts in creating and writing a research report in APA format. Requirements No Requirements needed to take this course. Description All students are consumers of research from psychology and other scientific disciplines. As such, it is important to develop your capacity for critically evaluating "scientific evidence" that is communicated in journals, magazines, newspapers, and news programs.This college level course is an introduction to the process of obtaining facts regarding social phenomena, social problems and problem solution commonly found in the social sciences. Students will be exposed to the wide range of social science research methods and designs, including observational methods, survey research, as well as correlation and experimental designs. Social science is the study of how people interact with one another. The branches of social science include anthropology, economics, political science, psychology, and sociology. Research methods are specific procedures for collecting and analyzing data. Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes.Learning ObjectivesDefine social science and research methods; Identify the stages of social research; Recognize the various types of research methods; Recognize influences in human behavior; Compare various theories of behavior; Define ethics as it pertains to ethical research; Identify ethical concerns within the research process; Recognize the professional codes of ethics; Increase awareness and sensitivity to ethical issues in research; Explain why it is necessary to consider ethical issues when designing and conducting research; Identify factors affecting problem selection; Recognize examples of current research; Develop ideas for research study; Explain influences on choosing a research design; Describe and develop research questions, frameworks, study designs, and measures appropriate for implementation science; Compare and contrast experimental and nonexperimental research; Identify types of nonexperimental research; Recognize technical terms in survey research methods; Compare and contrast between-subject and within-subject experimental design; Recognize non-survey data collection techniques; Recognize the various ways researchers describe data; Identify how validity and reliability are measured; Compare the quantitative / qualitative distinction; Explain the use of statistics in social science; Write in a clear and concise style; Gather relevant information from a variety of sources; Write an abstract that is appropriate for the target audience; Create and write a research report; Define terms relating to analysis and interpretation of research; Identify key methods in research reporting; Recognize presentation measures of association; and Compose social science research results. Who this course is for This is an introduction to a college level informational content course, intended to educate students about the basics of research methods used in psychology and the social sciences. Ideal to take before registering for your college Research Methods course. Homepage: https://www.udemy.com/course/research-methods-in-social-science-certificate/ [b]AusFile[/b] https://ausfile.com/0zcrkbtnsp74/wtfve.Research.Methods.in.Social.Science.Certificate.part1.rar.html https://ausfile.com/d6ora3q80pwm/wtfve.Research.Methods.in.Social.Science.Certificate.part2.rar.html https://ausfile.com/263x277oxig6/wtfve.Research.Methods.in.Social.Science.Certificate.part3.rar.html Rapidgator https://rg.to/file/21c113a5bc07c8d91150e4dc0400248c/wtfve.Research.Methods.in.Social.Science.Certificate.part1.rar.html https://rg.to/file/dd454fce404f9fd809ee5d142a8f3fd8/wtfve.Research.Methods.in.Social.Science.Certificate.part2.rar.html https://rg.to/file/9061a71e1a467a001dd50e968a8658bc/wtfve.Research.Methods.in.Social.Science.Certificate.part3.rar.html Fikper Free Download https://fikper.com/Kj98R694RF/wtfve.Research.Methods.in.Social.Science.Certificate.part1.rar.html https://fikper.com/z0BiSqDxIt/wtfve.Research.Methods.in.Social.Science.Certificate.part2.rar.html https://fikper.com/Qwm2MKnAXw/wtfve.Research.Methods.in.Social.Science.Certificate.part3.rar.html No Password - Links are Interchangeable

Free Download The Data Science Course - Complete Data Science Bootcamp 2025 Last updated: 1/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 15.87 GB | Duration: 31h 57m Complete Data Science Training: Math, Statistics, Python, Advanced Statistics in Python, Machine and Deep Learning What you'll learn The course provides the entire toolbox you need to become a data scientist Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow Impress interviewers by showing an understanding of the data science field Learn how to pre-process data Understand the mathematics behind Machine Learning (an absolute must which other courses don't teach!) Start coding in Python and learn how to use it for statistical analysis Perform linear and logistic regressions in Python Carry out cluster and factor analysis Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn Apply your skills to real-life business cases Use state-of-the-art Deep Learning frameworks such as Google's TensorFlowDevelop a business intuition while coding and solving tasks with big data Unfold the power of deep neural networks Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations Requirements No prior experience is required. We will start from the very basics You'll need to install Anaconda. We will show you how to do that step by step Microsoft Excel 2003, 2010, 2013, 2016, or 365 Description *Update 2025: Intro to Data Science module updated for recent AI developments*The ProblemData scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace. However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist. And how can you do that? Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming) Most online courses focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture The Solution Data science is a multidisciplinary field. It encompasses a wide range of topics. Understanding of the data science field and the type of analysis carried out Mathematics Statistics Python Applying advanced statistical techniques in Python Data Visualization Machine Learning Deep Learning Each of these topics builds on the previous ones. And you risk getting lost along the way if you don't acquire these skills in the right order. For example, one would struggle in the application of Machine Learning techniques before understanding the underlying Mathematics. Or, it can be overwhelming to study regression analysis in Python before knowing what a regression is. So, in an effort to create the most effective, time-efficient, and structured data science training available online, we created The Data Science Course 2024. We believe this is the first training program that solves the biggest challenge to entering the data science field - having all the necessary resources in one place. Moreover, our focus is to teach topics that flow smoothly and complement each other. The course teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs (not to mention the amount of time you will save). The Skills 1. Intro to Data and Data ScienceBig data, business intelligence, business analytics, machine learning and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean? Why learn it? As a candidate data scientist, you must understand the ins and outs of each of these areas and recognise the appropriate approach to solving a problem. This 'Intro to data and data science' will give you a comprehensive look at all these buzzwords and where they fit in the realm of data science. 2. Mathematics Learning the tools is the first step to doing data science. You must first see the big picture to then examine the parts in detail. We take a detailed look specifically at calculus and linear algebra as they are the subfields data science relies on. Why learn it? Calculus and linear algebra are essential for programming in data science. If you want to understand advanced machine learning algorithms, then you need these skills in your arsenal. 3. Statistics You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist. Why learn it? This course doesn't just give you the tools you need but teaches you how to use them. Statistics trains you to think like a scientist. 4. PythonPython is a relatively new programming language and, unlike R, it is a general-purpose programming language. You can do anything with it! Web applications, computer games and data science are among many of its capabilities. That's why, in a short space of time, it has managed to disrupt many disciplines. Extremely powerful libraries have been developed to enable data manipulation, transformation, and visualisation. Where Python really shines however, is when it deals with machine and deep learning.Why learn it? When it comes to developing, implementing, and deploying machine learning models through powerful frameworks such as scikit-learn, TensorFlow, etc, Python is a must have programming language. 5. TableauData scientists don't just need to deal with data and solve data driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must but be able to present and visualise the data's story in a way they will understand. That's where Tableau comes in - and we will help you become an expert story teller using the leading visualisation software in business intelligence and data science.Why learn it? A data scientist relies on business intelligence tools like Tableau to communicate complex results to non-technical decision makers. 6. Advanced Statistics Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, now these statistical methods are all performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail. Why learn it? Data science is all about predictive modelling and you can become an expert in these methods through this 'advance statistics' section. 7. Machine Learning The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work is what often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow. Why learn it? Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines. **What you get**A $1250 data science training program Active Q&A support All the knowledge to get hired as a data scientist A community of data science learners A certificate of completion Access to future updates Solve real-life business cases that will get you the job You will become a data scientist from scratch We are happy to offer an unconditional 30-day money back in full guarantee. No risk for you. The content of the course is excellent, and this is a no-brainer for us, as we are certain you will love it.Why wait? Every day is a missed opportunity.Click the "Buy Now" button and become a part of our data scientist program today. 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Free Download Udemy - Computational Science And Engineering 1 Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 4.61 GB | Duration: 5h 49m Applied Mathematics: Real World Modeling, Differential Equations, and Linear Systems What you'll learn Understand how to identify patterns and structures in a wide range of applications, including engineering, science, economics, and biology. Develop the ability to model real world problems using mathematical equations and techniques. Learn both analytical and numerical methods for solving mathematical equations, including the use of MATLAB. Gain experience in applying mathematical concepts to solve practical, real world problems. Requirements Basic understanding of calculus and differential equations, Some familiarity with MATLAB or a willingness to learn the software, Openness to learning linear algebra mathematical concepts and their applications in various fields Description This course on Computational Science and Engineering focuses on mathematical modeling, differential equations, and linear algebra to solve real-world problems. Students will learn to develop and analyze models for various applications in engineering, physics, and data science. Key topics include the use of the delta function, boundary value problems, and numerical methods.Through hands-on projects and case studies, parti[beeep]nts will gain practical skills in applying mathematical concepts to complex systems, enhancing their problem-solving abilities in diverse fields. The course emphasizes collaborative learning, where students work in teams to tackle real-world challenges, fostering teamwork and communication skills essential in today's workforce.Additionally, students will have access to software tools and programming languages commonly used in the industry, allowing them to implement and test their models effectively. Each module is designed to build upon the previous one, ensuring a comprehensive understanding of the material.By the end of the course, parti[beeep]nts will be equipped with the theoretical knowledge and practical experience needed to confidently approach complex mathematical problems. Join us to explore the intersection of theory and application in applied mathematics, and prepare to make significant contributions to your chosen field! This course concludes by encouraging questions for further clarification in subsequent sessions. 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Learn practical daily ways to work with crystals.Vibrations, chakras and powerful rocks! The truth about crystals!This course is the starting place for your 50 Lesson Accredited Certification Journey.Past students say:"A transformational experience! The Crystals & Crystal Healing Masterclass was truly a revelation for me. The information was presented clearly and in great detail, and the practical exercises gave me the confidence to apply the techniques professionally. The instructors were incredibly dedicated and answered all my questions thoroughly. This course not only deepened my knowledge about crystals but also helped me balance my own energies. I wholeheartedly recommend it to anyone interested in holistic healing!""Five star course! I am fascinated with the history of crystals and the cultures that have believed in their powers all throughout history. I learned that there is so much more to these beautiful rocks than I ever dreamed of!""The content was so clearly articulated and easy to follow. I loved listening and learning about the different crystals and their healing properties absolutely whet my appetite to continue learning." Overview Section 1: Welcome Lecture 1 Module 1 - Welcome Lecture 2 Defining Healing Lecture 3 Meet Your Instructors Lecture 4 Upgrade - Accredited Certification Path Lecture 5 Continued Education - Advanced Practitioner Level 2/3 Continued Education - Adva Section 2: Module 1: From The Heart of The Earth Lecture 6 Introduction to Module 1: From The Heart of The Earth Lecture 7 Lesson 01: How Crystals Are Born - Geological Formation Lecture 8 Lesson 02: The Recipe of a Crystal: Chemical Makeup and Mineral Composition Lecture 9 Lesson 03: The Magic Inside Crystals: Crystallography Lecture 10 Lesson 04: Natural Crystal Shapes & Healing Lecture 11 Lesson 05: Human Crafted Crystal Shapes & Healing Lecture 12 Lesson 06: Crystal Color Magic and Healing Powers Lecture 13 Lesson 07: Crystals Inner Strength: The Mohs Hardness Scale Lecture 14 Lesson 08: Not Just Shiny Rocks - Optical Properties of Crystal Healing Lecture 15 Lesson 09: Bringing It All Together Section 3: Module 2: Crystal Chronicles & Mysteries Lecture 16 Introduction to Module 2: Crystal Chronicles & Mysteries Lecture 17 Lesson 01: Crystal Lore & Stories Around The World Lecture 18 Lesson 02: Megalith Mysteries and Crystal Power Section 4: Module 3: Scientific Connections in Crystal Healing Lecture 19 Introduction to Module 3: Scientific Connections in Crystal Healing Lecture 20 Lesson 01: Earth Science & Crystal Connections Lecture 21 Lesson 02: Exploring Our Crystalline Biology Lecture 22 Lesson 03: Water Science & Crystal Connections Lecture 23 Lesson 04: Sacred Geometry & Crystal Connections Lecture 24 Lesson 05: Psychology & Crystal Connections Lecture 25 Lesson 06: Quantum Possibilities & Crystal Connections Lecture 26 Lesson 07: Crystals in Modern Medicine Section 5: Module 4: Choosing, Cleansing & Charging Your Crystals Lecture 27 Introduction to Module 04: Choosing, Cleansing & Charging Your Crystals Lecture 28 Lesson 01: The Resonance Factor: How Crystals Call to Us Lecture 29 Lesson 02: Cleansing Your Crystals Lecture 30 Lesson 03: Charging Your Crystals Lecture 31 Lesson 04: Storing Your Crystals Lecture 32 Lesson 05: Re-tuning Crystals Again & Again Section 6: Module 5: Healing Techniques with Crystals Lecture 33 Introduction to Module 05: Healing Techniques with Crystals Lecture 34 Lesson 01: The Power of Intention Lecture 35 Lesson 02: Channeling Energy Lecture 36 Lesson 03: Chakra Alignment Lecture 37 Lesson 04: Advanced Chakra Techniques Lecture 38 Lesson 05: Crystal Healing for Our Homes & Spaces Lecture 39 Lesson 06: Crystal Elixirs Lecture 40 Lesson 07: Crystal Jewelry for Healing Lecture 41 Lesson 08: Crystal Grids Section 7: Module 6: Essential Crystals Stones & Mineral Meanings Lecture 42 How To Work with Crystals Lecture 43 Amethyst Lecture 44 Aventurine Lecture 45 Black Tourmaline Lecture 46 Celestite Lecture 47 Citrine Lecture 48 Clear Quartz Lecture 49 Fluorite Lecture 50 Jasper Lecture 51 Labradorite Lecture 52 Lemurian Quartz Lecture 53 Lapis Lazuli Lecture 54 Larimar Lecture 55 Obsidian Lecture 56 Pyrite Lecture 57 Rose Quartz Lecture 58 Tektite Lecture 59 Selenite Lecture 60 Tiger's Eye Lecture 61 Yooperlite Section 8: Module 7: Crystal Programming & Meditations Lecture 62 Guided Meditation 01: Cleanse Your Crystal Lecture 63 Guided Meditation 02: Program Your Crystal Lecture 64 Guided Meditation 03: Rose Quartz Love Amplification Lecture 65 Guided Meditation 04: Citrine Abundance Meditation Lecture 66 Guided Meditation 05: Negative Energy Transmutation With Crystals Section 9: Module 8: Appendix of Crystal Tools & Resources Lecture 67 Crystal Course PDF Download Lecture 68 Alphabetical Crystal Quick Guide : A-E Lecture 69 Alphabetical Crystal Quick Guide : F-J Lecture 70 Alphabetical Crystal Quick Guide : K-O Lecture 71 Alphabetical Crystal Quick Guide : P-T Lecture 72 Alphabetical Crystal Quick Guide : U-Z Lecture 73 Crystal Selection Guide: A-Z for Every Need Lecture 74 Crystals Not Recommended for Water Lecture 75 Elements Within Crystals and Their Connection to Healing Lecture 76 Crystals That Fade In Sunlight Any wanting to learn about crystal healing for their joy or to grow their business and energy healing practices. 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Free Download Hair Coloring - Mastering the Art & Science of Hair Coloring Last updated: 1/2024 Created by: Leza Shahzad MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English + subtitle | Duration: 13 Lectures ( 36m ) | Size: 752 MB Theory What you'll learn Understanding safety protocols, expiry of products, potential allergic reactions, proper ventilation & the importance of patch testing to ensure client safety. Grasping the specific functions of each tool and how they contribute to the hair coloring process, from mixing colors to precise application. Recognizing and categorizing different hair textures such as fine, medium, coarse, straight, wavy, curly, or kinky. Understanding the structure of the hair, including the cuticle, cortex, and medulla, and how these components influence the hair's ability to retain color. Grasping the levels of hair pigmentation from levels 1 (black) to 10 (lightest blonde) including mix colors with their numbers. Learning about the color wheel, understanding primary and secondary colors and comprehending how these principles apply to hair coloring. Developing skills to identify and rectify color mistakes, understanding how to neutralize unwanted tones, and managing color fading or discrepancies. Recognizing and understanding different tones in hair, such as warm, cool, or neutral tones. Understanding Hair Levels with their underlying pigments and the anti colors for unwanted tones Understanding the different types of developers (peroxide) with the relationship between volume and the level of lifting achieved during the coloring process Learning the proper mixing ratios of developers with hair color to achieve the desired results. Requirements There are no Requirements other than having a notebook to take notes and desirable would be a dose of passion ;) Description Hello, I am a Aleeza a prof. Hair Artist, Certified, best hair Instructor on Udemy & Founder of Lezzaay Beauty Academy. I designed this Masterclass to teach you how to enter the hair Industry successfully.Picture a hair coloring theory course as a vibrant canvas where science meets artistry. It's a captivating journey that dives deep into the intricate world of hues, tones, and the magic of transformation.Throughout this journey, the students uncover the secrets of the color wheel, understanding how various shades, tones, and undertones interact to create breathtaking palettes.Ethics and professionalism are woven into the fabric of this course. Students are guided on maintaining a professional salon environment, respecting client confidentiality, and adhering to safety protocols when working with hair coloring products.Ultimately, this course isn't just a curriculum-it's a passage into a world where science meets artistry, where passion converges with skill, and where each stroke of color tells a unique story of beauty and self-expression.Certification: Obtaining recognized accreditation upon course completion.Career Paths: Exploring job opportunities in salons, freelance work, or starting a personal business.Enroll now & get taught all the fundamentals & expertise a Hair Colorist needs to know, to start a successful Career! Who this course is for Beginners: Those who wish to pursue their career as a hair artist or specialize in hair coloring within the beauty and cosmetology industry. Advanced: Salon professionals seeking to stay updated with the coloring theory, techniques, and knowledge in hair coloring. Individuals passionate about hair care and coloring who want to learn more about the science and art behind coloring techniques Homepage: https://www.udemy.com/course/mastering-the-art-and-science-of-hair-coloring/ Rapidgator https://rg.to/file/a25763ec5217512a408b0aed7cb9b0e1/vvtmn.Hair.Coloring.Mastering.the.Art..Science.of.Hair.Coloring.rar.html Fikper Free Download https://fikper.com/6SG4XaE8UP/vvtmn.Hair.Coloring.Mastering.the.Art..Science.of.Hair.Coloring.rar.html No Password - Links are Interchangeable