Overview

This repository serves as a comprehensive resource for aspirants of the Data Science career. This repository is designed to equip aspiring data scientists with the essential skills, knowledge, and hands-on experience required to excel in the field of data science.

What to Expect

In-depth training on core concepts, methodologies, and tools used in data science.
Engaging session slides and codes delivered by industry experts and experienced practitioners.
Practical exercises, projects, and case studies to reinforce learning.
Access to a supportive and collaborative learning environment.
Exclusive resources, code samples, and documentation for further reference.

Curriculum Highlights

Introduction to Data Science: Explore the foundations and principles of data science, its applications, and industry trends.
Data Manipulation and Analysis: Master data manipulation techniques using Python, including data cleaning, transformation, and exploratory analysis.
Machine Learning Essentials: Dive into the fundamentals of machine learning, including regression, classification, clustering, and evaluation.
Data Visualization: Learn to communicate insights effectively through impactful visualizations using popular libraries like Matplotlib and Seaborn.
Big Data and Cloud Computing: Discover techniques for handling large datasets and harnessing the power of cloud-based computing platforms.
Real-world Projects: Apply your knowledge to real-world projects, gaining practical experience and building a strong portfolio.

Who Should Get Benefit

Aspiring data scientists looking to kickstart their career in the field.
Professionals seeking to enhance their existing data analysis skills.
Students and researchers are interested in the intersection of data and technology.
Anyone passionate about leveraging data for impactful decision-making.

Get Involved

We encourage active participation and collaboration within this repository. Feel free to explore the code, contribute to ongoing projects, and engage with fellow boot camp participants. - -Together, we can build a vibrant and knowledge-sharing community.

Stay Connected With Me Connect with me on social media, stay up-to-date with the latest news, and continue learning.

LinkedIn: Mudasar Latif Memon, Ph.D.

Twitter: @mudaserlateef

Facebook: Mudasar Latif Memon

Bootcamp Resources Google Drive: Resources We're excited to embark on this data science journey with you and help you unlock your potential in this dynamic and rewarding field!

Happy coding! Engr. Dr. Mudasar Latif Memon

Name		Name	Last commit message	Last commit date
Latest commit History 57 Commits
week2		week2
week_1/day_1		week_1/day_1
D1.pdf		D1.pdf
D2.pdf		D2.pdf
D3.pdf		D3.pdf
D4.pdf		D4.pdf
D5.pdf		D5.pdf
Day13.ipynb		Day13.ipynb
K_mean_clustering.ipynb		K_mean_clustering.ipynb
Overfitting_Underfitting_analysis_for_non_parametric_classifiers_3.ipynb		Overfitting_Underfitting_analysis_for_non_parametric_classifiers_3.ipynb
PCA_and_LDA.ipynb		PCA_and_LDA.ipynb
README.md		README.md
day10_multi_variate_regression.ipynb		day10_multi_variate_regression.ipynb
day11_polynomial_regression.ipynb		day11_polynomial_regression.ipynb
day18_principal_component_analysis.ipynb		day18_principal_component_analysis.ipynb
day19_PCA_LDA_on_CIFAR_dataset_and_classification_using_SVM.ipynb		day19_PCA_LDA_on_CIFAR_dataset_and_classification_using_SVM.ipynb
day19_PCA_and_LDA.ipynb		day19_PCA_and_LDA.ipynb
day1_code.ipynb		day1_code.ipynb
day1_code.py		day1_code.py
day20_PCA_and_LDA_on_face_dataset_and_classification_using_SVM.ipynb		day20_PCA_and_LDA_on_face_dataset_and_classification_using_SVM.ipynb
day21_ANN_Artificial_neural_network.ipynb		day21_ANN_Artificial_neural_network.ipynb
day22_Skin_diseas_detection_using_ANN.ipynb		day22_Skin_diseas_detection_using_ANN.ipynb
day23_CNN_flower_classification.ipynb		day23_CNN_flower_classification.ipynb
day24_CNN_TSNE_Flower_Classification.ipynb		day24_CNN_TSNE_Flower_Classification.ipynb
day24_VGG_Flower_Classification.ipynb		day24_VGG_Flower_Classification.ipynb
day25_gui_digit_py.ipynb		day25_gui_digit_py.ipynb
day2_code.ipynb		day2_code.ipynb
day2_code.py		day2_code.py
day3_code.ipynb		day3_code.ipynb
day3_code.py		day3_code.py
day4_code.ipynb		day4_code.ipynb
day4_code.py		day4_code.py
day5_code.ipynb		day5_code.ipynb
day6_python_review.ipynb		day6_python_review.ipynb
day6_python_review_code.ipynb		day6_python_review_code.ipynb
day7_numpy.ipynb		day7_numpy.ipynb
day8_ML_salespred.ipynb		day8_ML_salespred.ipynb
day_12.ipynb		day_12.ipynb
day_12_part2.ipynb		day_12_part2.ipynb
day_14_naive_bayes.ipynb		day_14_naive_bayes.ipynb
day_16_random_forest.ipynb		day_16_random_forest.ipynb
day_17_Overfitting_Underfitting_analysis_for_non_parametric_classifiers_3.ipynb		day_17_Overfitting_Underfitting_analysis_for_non_parametric_classifiers_3.ipynb
day_18_Cross_validation.ipynb		day_18_Cross_validation.ipynb
day_18_principal_component_analysis_feature_compression.ipynb		day_18_principal_component_analysis_feature_compression.ipynb
day_25_MRI_brain_tumor_image_detection.ipynb		day_25_MRI_brain_tumor_image_detection.ipynb
day_9_lab_practice_linear_regression.ipynb		day_9_lab_practice_linear_regression.ipynb
matplot_practice.ipynb		matplot_practice.ipynb

MemonML/datascience_bootcamp

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Overview

What to Expect

Curriculum Highlights

Who Should Get Benefit

Get Involved

LinkedIn: Mudasar Latif Memon, Ph.D.

Twitter: @mudaserlateef

Facebook: Mudasar Latif Memon

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