Data Science for Beginners: Hands-On Data Science in Python (Udemy.com)
Learn TensorFlow 2.0, Deep Learning, Regression, Classification, Clustering, NPL, Data Analysis, Visualization and More
Created by: Vijay Gadhave
Produced in 2021
What you will learn
- The Complete Understanding of Machine Learning from the Scratch
- Learn Python for Data Science and Machine Learning
- Artificial Neural Networks (ANNs) with TensorFlow 2.0
- Convolutional Neural Networks (CNNs) with TensorFlow 2.0
- Deep Learning and Neural Networks
- Learn How to Pre-Process the Data
- Perform Linear and Logistic Regressions in Python
- Learn Different Regression Algorithms in Python
- Learn to Apply Different Classification Algorithms in Python
- K means and Hierarchical Cluster Analysis
- Data Analysis with NumPy and Pandas
- Data Visualization with Matplotlib library
- DataFrames, Pandas Series, Pandas Matrix
- NumPy Arrays, Indexing, Selection, Numpy Operations
- Learn to Work with Missing Data
- Natural Language Processing
- Dimensionality Reduction: PCA and LDA
Quality Score
Content Quality
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Video Quality
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Qualified Instructor
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Course Pace
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Course Depth & Coverage
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Overall Score : 92 / 100
Course Description
Data Science, Machine Learning and Artificial Intelligence are the most demanding skills in today's world,
Almost every Multi-National company is working on these new technologies
With this Mega Course you will learn all the required tools for Data Science from the very beginning !
We will cover below topics,
1) Data Pre-Processing: Importing Libraries, Importing Dataset, Working with missing data, Encoding categorical data, Splitting dataset into train and test set, Feature scaling
2) Regression Analysis: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Support Vector Machine, Decision Tree, Random Forest, Evaluating the Model Performance
3) Classification Techniques: Logistic Regression, KNN, SVM, Nave Bayes, Decision Tree, Random Forest
4) Cluster Analysis: K means, Hierarchical
5) Natural Language Processing: NLTK, Tokenization, Stemming, Lemmatization, Stop Words, POS Tagging, Chunking, Named Entity Recognition, Text Classification
6) Dimensionality Reduction: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA)
7) Artificial Neural Networks (ANNs) with TensorFlow 2.0
8) Convolutional Neural Networks (CNNs) with TensorFlow 2.0
9) Data Analysis with Numpy: NumPy Arrays, Indexing and Selection, NumPy Operations
10) Data Analysis with Pandas: Pandas Series, DataFrames, Multi-index and index hierarchy, Working with Missing Data, Groupby Function, Merging Joining and Concatenating DataFrames, Pandas Operations, Reading and Writing Files
11) Data Visualization with Matplotlib library
Learn Data Science to advance your Career and Increase your knowledge in a fun and practical way !
Regards,
Vijay GadhaveWho this course is for:
Almost every Multi-National company is working on these new technologies
With this Mega Course you will learn all the required tools for Data Science from the very beginning !
We will cover below topics,
1) Data Pre-Processing: Importing Libraries, Importing Dataset, Working with missing data, Encoding categorical data, Splitting dataset into train and test set, Feature scaling
2) Regression Analysis: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Support Vector Machine, Decision Tree, Random Forest, Evaluating the Model Performance
3) Classification Techniques: Logistic Regression, KNN, SVM, Nave Bayes, Decision Tree, Random Forest
4) Cluster Analysis: K means, Hierarchical
5) Natural Language Processing: NLTK, Tokenization, Stemming, Lemmatization, Stop Words, POS Tagging, Chunking, Named Entity Recognition, Text Classification
6) Dimensionality Reduction: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA)
7) Artificial Neural Networks (ANNs) with TensorFlow 2.0
8) Convolutional Neural Networks (CNNs) with TensorFlow 2.0
9) Data Analysis with Numpy: NumPy Arrays, Indexing and Selection, NumPy Operations
10) Data Analysis with Pandas: Pandas Series, DataFrames, Multi-index and index hierarchy, Working with Missing Data, Groupby Function, Merging Joining and Concatenating DataFrames, Pandas Operations, Reading and Writing Files
11) Data Visualization with Matplotlib library
Learn Data Science to advance your Career and Increase your knowledge in a fun and practical way !
Regards,
Vijay GadhaveWho this course is for:
- Students who want to start a career in the field of Data Science and Machine Learning
- Professionals who want to start a new career in Data Science
- Anyone who is interested in Machine Learning and Data science
- Data Analyst who want to level up in Machine Learning and Data Science
Instructor Details
- 4.6 Rating
37 Reviews
Vijay Gadhave
Hello Everyone,
I am Vijay Gadhave. I am a Data Scientist.
I have 5+ years of experience in the field of Data Science.
I have Professional experience of training students in the Field of Data Science and Software Development
I am passionate about various fields of Data Science, Software Development and instructing students/Professionals with the cutting edge technologies
Regards,
Vijay Gadhave
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Reviews
- Video Duration:
12h - Price: 11.99 Track Price 11.99 Track Price
- Provider: Udemy
- Year:
2021 - Language:
English, English [Auto-generated] - Certificate:
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