Master Data Science with 5-in-1 Projects for Interviews (2024)

2024 Master Data Science 5-in-1 Projects Data Interview ShowOff

Unleash the Power of Data: EDA, Sentiment Analysis, Predictive Modeling, Time Series Analysis & Big Data Analytics

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Last Updated: 2024-11-26 07:11:33 English Course Type: Self Learning

Understand the basics of data science, including statistics, probability, and data visualization techniques.
Learn how to clean and prepare your data for analysis.
Get hands-on experience with different data analysis techniques and learn how to interpret the results.
Dive into machine learning algorithms, understand how they work, and learn how to apply them in real-world situations.
Apply what you’ve learned in real-world projects, showcasing your skills to potential employers.

Embark on a transformative journey in data science with our comprehensive 5-in-1 project course. This course is meticulously designed to arm you with the skills needed to turn raw data into powerful insights and predictions.

Exploratory Data Analysis: Dive deep into the world of data exploration and visualization. Learn how to clean, preprocess, and draw meaningful insights from your datasets.

Sentiment Analysis: Uncover the underlying sentiments in text data. Master natural language processing techniques to classify text as positive, negative, or neutral.

Predictive Modeling: Predict the future today! Learn how to train machine learning models, evaluate their performance, and use them for future predictions.

Time Series Analysis: Step into the realm of time series data analysis. Learn how to preprocess and visualize time series data and build robust forecasting models.

Big Data Analytics: Scale up your data science skills with big data analytics. Learn how to process large datasets using Apache Spark in a distributed computing environment.

Enroll now and start your journey towards becoming a proficient data scientist! Unlock the power of data and transform your career. This course is perfect for beginners and professionals alike, providing hands-on projects that will reinforce your learning and give you real-world experience.

A computer and internet.
No programming experience needed.
You will learn everything you need to know.

Beginners: Those who are new to data science and want to understand the basics and build a strong foundation.
Intermediate Learners: Individuals who have some knowledge of data science but want to deepen their understanding and learn more advanced techniques.
Career Changers: Professionals from other fields who are interested in transitioning into a data science career.
Data Enthusiasts: Anyone with a keen interest in data and how it can be used to make informed decisions.
Job Seekers: Those who want to showcase their data science skills in job interviews.

Section 1 : Project 1 Google Play Store Data Analysis 6 Lectures 00:46:59
Lecture 1 :
Exploratory Data Analysis (EDA) of Google App Store Data Preview
Lecture 2 :
Data Visualization Techniques
Lecture 3 :
Statistical Analysis and Hypothesis Testing.
Lecture 4 :
Data Storytelling.
Lecture 5 :
Conclusion.
Lecture 6 :
Resources
Section 2 : Project 2 Sentiment Analysis NLP 6 Lectures 00:46:56
Lecture 1 :
Introduction to Sentiment Analysis _ NLP.
Lecture 2 :
Text Preprocessing for Sentiment Analysis.
Lecture 3 :
Feature Extraction for Sentiment Analysis
Lecture 4 :
Building Sentiment Analysis Models.
Lecture 5 :
Evaluation of Sentiment Analysis Models.
Lecture 6 :
Resources
Section 3 : Project 3 Predictive Modeling of The Titanic 5 Lectures 00:31:51
Lecture 1 :
Introduction to Predictive Modeling and Machine Learning
Lecture 2 :
Data Exploration and Preprocessing of the Titanic Dataset.
Lecture 3 :
Model Selection and Evaluation of The Titanic Dataset.
Lecture 4 :
Model Training and Hyperparameter Tuning of The Titanic Dataset.
Lecture 5 :
Deployment of Predictive Models of the Titanic Dataset.
Section 4 : Project 4 Time Series Analysis of Betcoin Historical Data dataset 5 Lectures 00:24:33
Lecture 1 :
Introduction
Lecture 2 :
Data Preprocessing and Cleaning.
Lecture 3 :
Visualizing Time Series Data.
Lecture 4 :
Creating Forecasting Models.
Lecture 5 :
Predicting Future Bitcoin Prices..
Section 5 : Project 5 Big Data Analytics of the New York City Taxi Trip Duration Dataset 5 Lectures 00:20:55
Lecture 1 :
Introduction to Big Data Analytics of the New York City Taxi Trip Duration..
Lecture 2 :
Big Data Data Exploration and Preprocessing.
Lecture 3 :
Big Data Transformation and Feature Engineering
Lecture 4 :
Big Data Visualization and Analysis.
Lecture 5 :
Big Data Analytics Conclusion and Next Steps.

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Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic.
Can i play & pause the course as per my convenience?
Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
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Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want.
Do i need a pc to access the course or can i do it on mobile & tablet as well?
Brilliant question? Isn't it? You can access the courses on any device like PC, Mobile, Tablet & even on a smart tv. For mobile & a tablet you can download the Learnfly android or an iOS app. If mobile app is not available in your country, you can access the course directly by visting our website, its fully mobile friendly.
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Hello there! With over 350,000 happy students enrolled in my courses, I'm thrilled to be sharing my programming and data science expertise with you. As a programmer and data scientist, I've mastered several programming languages, including Python, SQL, JavaScript, R Programming, as well as tools like Excel, Tableau, Jupyter Notebook, Apache Cassandra, Apache Spark, Apache Airflow, Apache Kafka, AWS, and R Studio. I'm passionate about teaching and sharing my knowledge with the community. When I'm not coding, you can usually find me hiking or reading a good book. I believe that lifelong learning is essential for personal development, and my courses are designed to encourage students to continue learning outside of formal education. I update my courses every month to add new sections based on your feedback and requests. So don't wait – enroll in my courses now and start your journey towards mastering programming, web development, data science, data Engineering and Machine Learning!