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Programming for Data Science - CBT Nuggets
English | Size: 12.25 GB
Genre: eLearning
Programming for Data Science Online Training
This intermediate Programming for Data Science training prepares learners to write code that makes sense of unstructured sets from multiple channels and sources and processes information you need, how you need it.
Coding and programming is fundamental to data science. If you want a career in data science, you have to plan on learning at least one or two programming languages, or else prepare yourself for a job hemmed in and restricted by whatever programs you happen to get your hands on.
When you learn programming for data science, you unlock the power of making your data do exactly what you’d like it to do for you. Without programming, your results and findings are dependent on someone else’s program and code — unlock your own future in data science by learning a programming language.
Once you’re done with this Programming for Data Science training, you’ll know how to write code that makes sense of unstructured sets from multiple channels and sources and processes information you need, how you need it.
For anyone who leads an IT team, this Data Science training can be used to onboard new data analysts, curated into individual or team training plans, or as a Data Science reference resource.
Programming for Data Science: What You Need to Know
This Programming for Data Science training has videos that cover topics including:
Writing reusable Python functions for data science
Writing Python code using object-oriented programming (OOP)
Wrangling data with Numpy and Pandas
Visualizing data with Matplotlib and Seaborn
Who Should Take Programming for Data Science Training?
This Programming for Data Science training is considered associate-level Data Science training, which means it was designed for data analysts and data scientists. This data science skills course is designed for data analysts with three to five years of experience with data science.
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CBT Nuggets - Programming for Data Science
1. Explore Data Science Domains and Roles
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1. Explore Data Science Domains and Roles .mp4 (24.1 MB)
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2. What is Data Science .mp4 (95.4 MB)
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3. Data Science Tools .mp4 (102.3 MB)
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4. Data Science Development Environments .mp4 (83.6 MB)
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5. What is Anaconda .mp4 (48.4 MB)
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6. Data Science Roles .mp4 (43.4 MB)
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7. The Data Science Roadmap .mp4 (61.1 MB)
10. Write Code using OOP Concepts for Data Science
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1. Introduction .mp4 (125.1 MB)
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2. Programming Styles .mp4 (123.8 MB)
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3. Python Class Objects .mp4 (169.4 MB)
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4. EDA Dimensions .mp4 (66.5 MB)
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5. EDA Summary Statistics .mp4 (74.5 MB)
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6. EDA Complete with Histograms .mp4 (60.2 MB)
11. Wrangling Data with Pandas for Data Science
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1. Introduction .mp4 (75.4 MB)
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2. What is Pandas Part 1 .mp4 (79.1 MB)
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3. What is Pandas Part 2 .mp4 (71.6 MB)
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4. EDA (Exploratory Data Analysis) .mp4 (85.6 MB)
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5. Clean and Manipulate Data .mp4 (96.4 MB)
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6. Data Visualization with Pandas (it does that also!) .mp4 (103.3 MB)
12. Work with Arrays Using Numpy Data Science Library
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1. Introduction -3.mp4 (99.7 MB)
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2. What is Numpy .mp4 (52.9 MB)
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3. Numpy Vs Pandas .mp4 (95.0 MB)
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4. Creating and Manipulating Arrays .mp4 (63.2 MB)
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5. Array Operations, Array Methods and Functions .mp4 (67.6 MB)
13. Visualizing Data with Matplotlib for Data Science
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1. Introduction .mp4 (36.1 MB)
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2. What is Matplotlib .mp4 (161.5 MB)
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3. Fields in the dataset from Kaggle .mp4 (155.4 MB)
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4. Customizing Plots .mp4 (80.0 MB)
14. Visualize Data with Seaborn for Data Science
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1. Introduction -3.mp4 (69.4 MB)
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2. Matplotlib vs Seaborn .mp4 (149.4 MB)
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3. Plotting with Seaborn .mp4 (92.9 MB)
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4. Customizing Plots .mp4 (82.1 MB)
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5. Real-world Notebook .mp4 (22.0 MB)
15. Explore Web Scraping Fundamentals for Data Science
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1. Introduction .mp4 (26.9 MB)
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2. How the Internet Works .mp4 (39.2 MB)
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3. Visual Studio Code .mp4 (97.0 MB)
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4. HTML .mp4 (45.7 MB)
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5. CSS .mp4 (53.3 MB)
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6. Web Scraping with BeautifulSoup .mp4 (148.9 MB)
16. Collect Web Data with Python and BeautifulSoup
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1. Introduction .mp4 (55.1 MB)
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2. What is BeautifulSoup .mp4 (34.0 MB)
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3. The find() Method Part 1 .mp4 (91.8 MB)
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4. The find() Method Part 2 .mp4 (129.4 MB)
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5. The find_all() Method Part 1 .mp4 (135.7 MB)
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6. The find_all() Method Part 2 .mp4 (82.3 MB)
17. Use GitHub Repositories for Data Science
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1. Introduction -2.mp4 (38.4 MB)
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2. What is Git .mp4 (61.2 MB)
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3. What is GitHub .mp4 (62.0 MB)
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4. Create an Online Repo and Push Your Code to GitHub .mp4 (84.8 MB)
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5. Hosting Datasets for use in Jupyter Notebook .mp4 (94.0 MB)
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6. Challenge .mp4 (28.9 MB)
18. Analyze Core Data Structures for Data Science
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1. Introduction .mp4 (133.0 MB)
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2. What are Data Structures .mp4 (85.2 MB)
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3. Python Basic Data Structure Limitations .mp4 (124.7 MB)
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4. Data Structures Deep Dive .mp4 (141.5 MB)
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5. Social Network Analysis Use Case .mp4 (118.3 MB)
19. Evaluate Complexity and Memory for Data Science
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1. Introduction - Programming for Data Science CBT Nuggets-3.mp4 (144.0 MB)
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2. Complexity Analysis and Memory .mp4 (93.5 MB)
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3. Algorithm Comparison .mp4 (121.9 MB)
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4. Pandas Data Types .mp4 (210.6 MB)
2. Access the Command Line for Data Science
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1. Introduction .mp4 (170.8 MB)
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2. What is a command-line, terminal, and Shell .mp4 (137.4 MB)
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3. macOS Terminal, Git for Windows, and Linux Emulators .mp4 (80.9 MB)
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4. Basic Linux Commands .mp4 (105.6 MB)
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5. Create Projects and Workflows .mp4 (83.0 MB)
20. Apply Big O Notation Concepts for Data Science
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1. Introduction .mp4 (131.8 MB)
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2. Big O Notation .mp4 (57.4 MB)
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3. Big O Notation and Time Complexity Visualization .mp4 (57.1 MB)
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4. Quadratic time .mp4 (38.2 MB)
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5. Factorial time .mp4 (132.6 MB)
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6. Coffee Shop Complexity .mp4 (109.6 MB)
21. Explore R Fundamentals for Data Science
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1. Introduction -3.mp4 (193.7 MB)
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2. What is R and Why Should I Learn it in 2023 .mp4 (167.8 MB)
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3. Getting Started with R and Google Colab .mp4 (176.8 MB)
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4. R Data Types .mp4 (101.0 MB)
22. Implement and Compare R Data Structures
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1. Introduction .mp4 (117.7 MB)
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2. R and Python Data Structures Part 1 Vectors .mp4 (57.2 MB)
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3. R and Python Data Structures Part 2 Arrays and Lists .mp4 (40.5 MB)
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4. R and Python Data Structures Part 3 Data Frames .mp4 (30.8 MB)
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5. Operations and Calculations .mp4 (59.3 MB)
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6. Matrix Calculations .mp4 (76.2 MB)
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7. Data Exploration .mp4 (133.4 MB)
23. Perform EDA with R and Python for Data Science
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1. Introduction .mp4 (19.1 MB)
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2. Load and Prepare the Dataset (EDA light) .mp4 (104.5 MB)
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3. Perform Exploratory Data Analysis (EDA) Part II .mp4 (116.1 MB)
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4. Perform Exploratory Data Analysis (EDA) Part I .mp4 (76.3 MB)
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5. Challenge .mp4 (74.7 MB)
24. Explore AI Language Models and OpenAI's ChatGPT
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1. Introduction.mp4 (71.6 MB)
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2. What is AI.mp4 (131.1 MB)
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3. OpenAI GPT-3 Language Models.mp4 (67.4 MB)
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4. What is ChatGPT and How Does it Work Under the Hood.mp4 (35.4 MB)
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5. Prompts and Completions.mp4 (185.4 MB)
25. Query OpenAI's Language Model API with Google's Colab
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