100 Days Data Science Bootcamp: Build 100 Real Life Projects

所在平台: Udemy

课程主页: https://www.udemy.com/course/real-world-data-science-projects/

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课程简介

课程名称:100天数据科学训练营:构建100个真实项目 概述: 本课程旨在通过实践解决商业问题,学习如何构建和部署机器学习、数据科学、人工智能、自动机器学习、深度学习、自然语言处理等相关的Web应用项目,使用Python编程语言(Flask、Django、Heroku、AWS、Azure、GCP、IBM Watson、Streamlit Cloud)。根据Glassdoor的数据显示,数据科学家的年均工资为$117,345,远超国家平均工资的$44,564,这使得数据科学成为一个高度盈利的职业选择。由于数据科学家稀缺,导致这个领域的收入泡沫。 数据科学的学习曲线较陡峭,要求从业者在统计学、数学和计算机科学等多个领域具备扎实的知识,因此,数据科学家的市场价值相对较高。数据科学家在公司中享有一定的声望,他们的专业知识帮助公司做出基于数据的决策,指引公司向前发展。 数据科学家的薪资和所担任职务、工作内容及公司规模都有关系。虽然数据科学家的薪资普遍高于其他IT和管理领域,但这也与他们需要投入的工作量成正比。因此,数据科学是一项需要努力学习的职业。 课程的亮点在于参与100个真实项目的实践,项目包括但不限于: 1. 驾驶证伪造检测应用 2. 狗品种预测Flask应用 3. 交通标志分类 4. 文本识别应用 5. 动植物病害预测 6. 面部识别与交换应用 7. 情感分析和推荐系统 8. 银行客户流失预测 9. 聊天机器人创建 10. 房屋价格预测等。 建议的学习计划是制定50天或100天的学习计划,每天花费1-3小时,完成100个项目。这是成为数据科学家、被雇用并开启新职业生涯的最佳课程,建议尽早报名,享受优惠。 课程内容涵盖了数据科学的广泛应用,使学员具备扎实的实战能力,为未来职业发展打下坚实基础。

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课程详情

In This Course, Solve Business Problems Using Data Science Practically. Learn To Build & Deploy Machine Learning, Data Science, Artificial Intelligence, Auto Ml, Deep Learning, Natural Language Processing (Nlp) Web Applications Projects With Python (Flask, Django, Heroku, AWS, Azure, GCP, IBM Watson, Streamlit Cloud).According to Glassdoor, the average salary for a Data Scientist is $117,345/yr. This is above the national average of $44,564. Therefore, a Data Scientist makes 163% more than the national average salary.This makes Data Science a highly lucrative career choice. It is mainly due to the dearth of Data Scientists resulting in a huge income bubble.Since Data Science requires a person to be proficient and knowledgeable in several fields like Statistics, Mathematics, and Computer Science, the learning curve is quite steep. Therefore, the value of a Data Scientist is very high in the market.A Data Scientist enjoys a position of prestige in the company. The company relies on its expertise to make data-driven decisions and enable them to navigate in the right direction.Furthermore, the role of a Data Scientist depends on the specialization of his employer company. For example - A commercial industry will require a data scientist to analyze their sales.A healthcare company will require data scientists to help them analyze genomic sequences. The salary of a Data Scientist depends on his role and type of work he has to perform. It also depends on the size of the company which is based on the amount of data they utilize.Still, the pay scale of Data scientists is way above other IT and management sectors. However, the salary observed by Data Scientists is proportional to the amount of work that they must put in. Data Science needs hard work and requires a person to be thorough with his/her skills.Due to several lucrative perks, Data Science is an attractive field. This, combined with the number of vacancies in Data Science makes it an untouched gold mine. Therefore, you should learn Data Science in order to enjoy a fruitful career.In This Course, We Are Going To Work On 100 Real World Projects Listed Below:Project-1: Pan Card Tempering Detector App -Deploy On HerokuProject-2: Dog breed prediction Flask AppProject-3: Image Watermarking App -Deploy On HerokuProject-4: Traffic sign classificationProject-5: Text Extraction From Images ApplicationProject-6: Plant Disease Prediction Streamlit AppProject-7: Vehicle Detection And Counting Flask AppProject-8: Create A Face Swapping Flask AppProject-9: Bird Species Prediction Flask AppProject-10: Intel Image Classification Flask AppProject-11: Language Translator App Using IBM Cloud Service -Deploy On HerokuProject-12: Predict Views On Advertisement Using IBM Watson -Deploy On HerokuProject-13: Laptop Price Predictor -Deploy On HerokuProject-14: WhatsApp Text Analyzer -Deploy On HerokuProject-15: Course Recommendation System -Deploy On HerokuProject-16: IPL Match Win Predictor -Deploy On HerokuProject-17: Body Fat Estimator App -Deploy On Microsoft AzureProject-18: Campus Placement Predictor App -Deploy On Microsoft AzureProject-19: Car Acceptability Predictor -Deploy On Google CloudProject-20: Book Genre Classification App -Deploy On Amazon Web ServicesProject 21: DNA classification for finding E.Coli - Deploy On AWSProject 22: Predict the next word in a sentence. - AWS - Deploy On AWSProject 23: Predict Next Sequence of numbers using LSTM - Deploy On AWSProject 24: Keyword Extraction from text using NLP - Deploy On AzureProject 25: Correcting wrong spellings - Deploy On AzureProject 26: Music popularity classification - Deploy On Google App EngineProject 27: Advertisement Classification - Deploy On Google App EngineProject 28: Image Digit Classification - Deploy On AWSProject 29: Emotion Recognition using Neural Network - Deploy On AWSProject 30: Breast cancer Classification - Deploy On AWSProject-31: Sentiment Analysis Django App -Deploy On HerokuProject-32: Attrition Rate Django ApplicationProject-33: Find Legendary Pokemon Django App -Deploy On HerokuProject-34: Face Detection Streamlit AppProject-35: Cats Vs Dogs Classification Flask AppProject-36: Customer Revenue Prediction App -Deploy On HerokuProject-37: Gender From Voice Prediction App -Deploy On HerokuProject-38: Restaurant Recommendation SystemProject-39: Happiness Ranking Django App -Deploy On HerokuProject-40: Forest Fire Prediction Django App -Deploy On HerokuProject-41: Build Car Prices Prediction App -Deploy On HerokuProject-42: Build Affair Count Django App -Deploy On HerokuProject-43: Build Shrooming Predictions App -Deploy On HerokuProject-44: Google Play App Rating prediction With Deployment On HerokuProject-45: Build Bank Customers Predictions Django App -Deploy On HerokuProject-46: Build Artist Sculpture Cost Prediction Django App -Deploy On HerokuProject-47: Build Medical Cost Predictions Django App -Deploy On HerokuProject-48: Phishing Webpages Classification Django App -Deploy On HerokuProject-49: Clothing Fit-Size predictions Django App -Deploy On HerokuProject-50: Build Similarity In-Text Django App -Deploy On HerokuProject-51: Black Friday Sale ProjectProject-52: Sentiment Analysis ProjectProject-53: Parkinson's Disease Prediction ProjectProject-54: Fake News Classifier ProjectProject-55: Toxic Comment Classifier ProjectProject-56: IMDB Movie Ratings PredictionProject-57: Indian Air Quality PredictionProject-58: Covid-19 Case AnalysisProject-59: Customer Churning PredictionProject-60: Create A ChatBotProject-61: Video Game sales AnalysisProject-62: Zomato Restaurant AnalysisProject-63: Walmart Sales ForecastingProject-64: Sonic wave velocity prediction using Signal Processing TechniquesProject-65: Estimation of Pore Pressure using Machine LearningProject-66: Audio processing using MLProject-67: Text characterisation using Speech recognitionProject-68: Audio classification using Neural networksProject-69: Developing a voice assistantProject-70: Customer segmentationProject-71: FIFA 2019 AnalysisProject-72: Sentiment analysis of web scrapped dataProject-73: Determining Red Vine QualityProject-74: Customer Personality AnalysisProject-75: Literacy Analysis in IndiaProject-76: Heart Attack Risk Prediction Using Eval ML (Auto ML)Project-77: Credit Card Fraud Detection Using Pycaret (Auto ML)Project-78: Flight Fare Prediction Using Auto SK Learn (Auto ML)Project-79: Petrol Price Forecasting Using Auto KerasProject-80: Bank Customer Churn Prediction Using H2O Auto MLProject-81: Air Quality Index Predictor Using TPOT With End-To-End Deployment (Auto ML)Project-82: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)Project-83: Pizza Price Prediction Using ML And EVALML(Auto ML)Project-84: IPL Cricket Score Prediction Using TPOT (Auto ML)Project-85: Predicting Bike Rentals Count Using ML And H2O Auto MLProject-86: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)Project-87: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)Project-88: Hospital Mortality Prediction Using PyCaret (Auto ML)Project-89: Employee Evaluation For Promotion Using ML And Eval Auto MLProject-90: Drinking Water Potability Prediction Using ML And H2O Auto MLProject-91: Image Editor Application With OpenCV And TkinterProject-92: Brand Identification Game With Tkinter And Sqlite3Project-93: Transaction Application With Tkinter And Sqlite3Project-94: Learning Management System With DjangoProject-95: Create A News Portal With DjangoProject-96: Create A Student Portal With DjangoProject-97: Productivity Tracker With Django And PlotlyProject-98: Create A Study Group With DjangoProject-99: Building Crop Guide Application with PyQt5, SQLiteProject-100: Building Password Manager Application With PyQt5, SQLiteTip: Create A 50 Days Study Plan Or 100 Day Study Plan, Spend 1-3hrs Per Day, Build 100 Projects In 50 Days Or 100 Projects In 100 Days.The Only Course You Need To Become A Data Scientist, Get Hired And Start A New CareerNote (Read This): This Course Is Worth Of Your Time And Money, Enroll Now Before Offer Expires.

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