Tag: Jupyter Notebook setup

1.1 Installing Python and Choosing an IDE Jupyter Notebook, JupyterLab, PyCharm, VS Code and IDLE Differences, official websites, installation steps, commands, shortcuts and classroom practice Learning outcomes Explain the difference between Python, an interpreter, a package manager, a notebook, a code editor, and an IDE. Select Jupyter Notebook, PyCharm, VS Code, or IDLE according to the task. Install and verify Python using safe commands. Launch Jupyter Notebook and create, run, save, and close a notebook correctly. Create and run a Python file in PyCharm or VS Code. Use common package-management commands and important keyboard shortcuts. Recognize and solve beginner problems such as 'Python not found,' 'Jupyter not found,' and ModuleNotFoundError. Contents at a glance 1. Essential terms and how the tools work together 2. Text editor versus IDE 3. Difference between Python, Anaconda, Jupyter, IDLE, PyCharm and VS Code 4. Which tool should be used for which purpose? 5. Official websites and safe downloads 6. Route A: Anaconda + Jupyter (recommended for the workshop) 7. Route B: Python.org + pip + Jupyter 8. Installing and using PyCharm 9. Installing and using VS Code 10. Commands and shortcuts 11. Common errors and solutions 12. Guided practical, revision and glossary 1. Essential terms: understand these before installation Most important idea: Python is the language and interpreter. Jupyter Notebook, PyCharm, and VS Code are interfaces in which we write and run Python. Installing an IDE alone does not always install Python. TermEasy meaningPythonA programming language. The Python interpreter reads and executes Python instructions.InterpreterThe program that actually executes Python code. Without a working interpreter, the Run button cannot execute Python.IDEIntegrated Development Environment: one application that combines editing, running, debugging, project tools and code assistance.Code editorA flexible text editor designed for code. Extra features are commonly added through extensions.NotebookAn interactive document made of cells. It can contain code, Markdown explanation, output, equations and charts.KernelThe running computational process behind a Jupyter notebook. It stores variables and executes cells.Package / libraryReusable code written by others, such as pandas for data tables or matplotlib for graphs.pipPython's package installer. It downloads and installs Python packages into a selected interpreter/environment.condaA package and environment manager supplied with Anaconda/Miniconda. It can manage Python and non-Python dependencies.EnvironmentAn isolated place containing a particular Python version and packages for one course or project. Figure 1. The IDE/notebook provides the workspace; the Python interpreter performs the execution. File types you will see ExtensionMeaningWhere commonly used.pyA Python script file. It usually runs from top to bottom.IDLE, PyCharm, VS Code, terminal.ipynbA Jupyter notebook containing cells, outputs and metadata.Jupyter Notebook, JupyterLab, VS Code, PyCharm.csvA comma-separated data file.pandas, Excel, notebooks.txtA plain text file.Any text editor or IDE 2. Text editor versus IDE A plain text editor can write code, but it normally does not understand the complete Python project. An IDE adds tools that help us write, test and correct programs. VS Code starts as a code editor but becomes IDE-like after installing Python and Jupyter extensions. FeaturePlain text editorIDE / IDE-like setupWrite textYesYesSyntax coloursUsually limitedYesAutomatic suggestionsUsually noYes: autocomplete / IntelliSenseRun codeUsually requires a terminal commandRun button and terminal optionsFind errorsMostly manualWarnings, linting and error highlightingDebug step by stepUsually noYes: breakpoints, step-over, variable viewManage projectsBasic files onlyFolders, interpreters, tests and version controlComputer resourcesVery lightUsually heavier Advantages of an IDE over a plain text editor Syntax highlighting makes keywords, strings, numbers, and comments visually different. Autocomplete reduces typing and spelling mistakes. Immediate error indicators help students locate missing brackets, incorrect indentation, and undefined names. A Run button executes code without repeatedly typing a terminal command. A debugger can pause the program and show how variables change line by line. Interpreter selection helps a project use the correct Python installation and packages. Project navigation, search, refactoring, testing, and Git support become available in one place. Balanced view: A text editor is still useful for very small changes and for learning command-line execution. An IDE is not 'better for every task'; it is better when its assistance saves time or prevents mistakes. 3. Difference between the available tools ToolWhat it isBest useMain fileRememberPythonLanguage + interpreterRunning Python code.pyEssential; not an IDEAnaconda DistributionPython distributionEasy scientific/data setupManyIncludes Python, conda, Jupyter and many packagesAnaconda NavigatorGraphical launcherOpening Jupyter and managing environments without commandsN/ANot an IDE and not Python itselfIDLESimple editor + shellFirst tiny scripts and immediate experiments.pyUsually installed with Python from python.orgJupyter NotebookInteractive notebookTeaching, data analysis, graphs and explanations.ipynbBest starting point for this workshopJupyterLabAdvanced notebook workspaceMultiple notebooks, files, terminals and data.ipynbMore powerful interface than classic NotebookPyCharmFull Python IDEStructured Python projects and debugging.py / .ipynbPython-focused and feature-richVS CodeExtensible code editorPython plus many other languages and tools.py / .ipynbNeeds Python and extensions configured Jupyter Notebook versus JupyterLab PointJupyter NotebookJupyterLabInterfaceFocused on one notebookWorkspace with tabs, file browser, terminals and notebooksBeginner learningVery easyEasy, but has more visible optionsLarge data workflowAdequateMore convenientCommandsjupyter notebookjupyter labFile format.ipynb.ipynb 4. Which tool should be used for what purpose? SituationRecommended toolReasonFirst B.Pharm practical classJupyter NotebookStudents can see code, explanation, and output together.Biostatistics, data tables and graphsJupyter Notebook or JupyterLabInteractive analysis and visual output are convenient.Very first five-line Python scriptIDLE or JupyterMinimum setup and fewer distractions.Larger multi-file Python applicationPyCharmStrong project structure, refactoring, and debugging.Python plus HTML, SQL, R, JavaScript or other toolsVS CodeOne flexible editor can support many languages through extensions.Institution-managed laboratoryPython.org + venv + pip, or an institution-approved distributionThe institution can control versions, licensing, and packages.Low-storage computerPython.org + IDLE, or MinicondaSmaller than the full Anaconda Distribution. Simple recommendation: For this B.Pharm course, start with Jupyter Notebook. Later, introduce VS Code or PyCharm after students understand variables, operators, strings, conditions, and loops. 5. Official websites and safe downloads Always download software from the official website. Search advertisements and third-party download pages may provide old, modified or bundled installers. ProductOfficial websitePurposePythonhttps://www.python.org/downloads/Python interpreter and IDLEJupyterhttps://jupyter.org/installOfficial pip/conda installation commandsAnaconda Distributionhttps://www.anaconda.com/downloadPython, conda, Jupyter and data-science packagesAnaconda install guidehttps://www.anaconda.com/docs/getting-started/anaconda/install/windows-gui-installWindows graphical installation stepsPyCharmhttps://www.jetbrains.com/pycharm/download/Python-focused IDEVS Codehttps://code.visualstudio.com/downloadCross-platform code editorVS Code Python tutorialhttps://code.visualstudio.com/docs/python/python-tutorialPython interpreter, extension and editor setupIDLE documentationhttps://docs.python.org/3/library/idle.htmlIDLE editor and shell Important Anaconda note: Anaconda's current website includes licensing conditions for some organizations. A college or institution should review the current Terms of Service before a laboratory-wide deployment. Python, Jupyter, and pip can also be installed directly without the full Anaconda Distribution. 6. Route A - Install Anaconda and use Jupyter Notebook Recommended classroom route: This is usually the easiest route for beginners because one installer supplies Python, Conda, Jupyter Notebook, JupyterLab, and many scientific packages. Use this route only after the individual or institution accepts the current Anaconda terms. A. Before installation Use a Windows 10 or Windows 11 computer with sufficient free space. Save or close important work before installation. Remove incomplete older Anaconda installations if they are causing conflicts; do not delete working environments without backup. Decide on a simple course folder, for example, Documents\BPharm_Python. Do not install a second Python distribution unless you understand how to select interpreters and environments. B. Download and install on Windows Step 1—Open the official download page Visit https://www.anaconda.com/download and choose the Windows 64-bit graphical installer appropriate for the computer. Step 2—Start the installer Open the downloaded .exe file from the Downloads folder. If Windows asks for permission, verify the publisher and continue. Step 3 - Accept the license terms Read the current terms and select I Agree only if they are acceptable for the intended use. Step 4 - Choose the user scope For a personal student computer, 'Just Me' normally avoids administrator and permission problems. Step 5—Choose a simple location Keep the suggested location or use a folder without special characters. The official guide advises avoiding spaces or special characters where possible. Step 6: Complete installation Keep the default options unless the institution provides different instructions. Finish the installer, then open Anaconda Navigator or Anaconda Prompt from the Start menu. C. Verify the installation Open Anaconda Prompt from the Windows Start menu. Type one command at a time and press Enter. Verification commands conda --versionpython --versionjupyter --version A version number means the command was found. The exact number may differ from the examples shown in class; that is normal. D. Create the course folder and open Jupyter Commands in Anaconda Prompt cd %USERPROFILE%\Documentsmkdir BPharm_Pythoncd BPharm_Pythonjupyter notebook The command starts a local Jupyter server and normally opens the file browser in your default web browser. The address usually begins with http://localhost:. This does not mean the notebook is stored on a public website; the program is running on your computer. Do not close the prompt immediately: The Anaconda Prompt window is running the Jupyter server. Save your notebook, use File > Shut Down or close the notebook interface as appropriate, then return to the prompt and press Ctrl+C (confirm if asked) to stop the server. E. Open Jupyter without commands Open Anaconda Navigator from the Start menu. Find Jupyter Notebook or JupyterLab. Select Launch. Navigate to the BPharm_Python folder. Create a new Python notebook. F. Create and run the first notebook Select New > Python 3 (or the available Python kernel). Rename the notebook from Untitled to 01_First_BPharm_Program. Click the first code cell and type the program below. Press Shift+Enter to run the cell. Check the output and save the notebook with Ctrl+S. First B.Pharm example medicine_name = "Paracetamol"tablet_strength_mg = 500print("Medicine:", medicine_name)print("Strength:", tablet_strength_mg, "mg") Expected output: Medicine: Paracetamol and Strength: 500 mg. The value 500 is only a programming example; it is not a prescribing or dosing instruction. G. Create an optional course environment An environment keeps the course packages separate from unrelated projects. For a very first class, the base environment may be used if the faculty has already prepared it. For a clean setup, use: Optional environment commands conda create -n bpharm_python pythonconda activate bpharm_pythonconda install jupyter numpy pandas matplotlib seaborn scipyjupyter notebook To leave the environment later, use conda deactivate. The environment name bpharm_python can be changed, but avoid spaces. 7. Route B—Install Python from python.org and add Jupyter Use this route when: You want a smaller, direct setup; the institution does not want the full Anaconda Distribution; or you want to learn standard Python, venv, and pip commands. A. Install Python Step 1 - Download Python Go to https://www.python.org/downloads/ and choose the latest stable Python 3 installer supported by your operating system. Step 2—Run the installer On a traditional Windows installer, select the option that makes Python available from the command line (commonly shown as Add python.exe to PATH). Newer installer experiences may present this differently. Step 3—Complete installation Keep the standard components, including pip and IDLE, unless institutional policy says otherwise. Step 4 - Open a new terminal Close old Command Prompt windows and open a fresh Command Prompt or PowerShell so the updated command path is loaded. B. Verify Python and pip Preferred Windows commands py --versionpy -m pip --version If the py command is unavailable but Python works, use `python --version` and `python -m pip --version` instead. Using python -m pip is safer than typing only pip because it connects pip to the selected interpreter. C. Create a virtual environment Windows Command Prompt cd %USERPROFILE%\Documentsmkdir BPharm_Pythoncd BPharm_Pythonpy -m venv bpharm_envbpharm_env\Scripts\activate After activation, the prompt normally shows (bpharm_env). PowerShell may require a different activation command or an institution-approved execution policy; use the local IT policy rather than bypassing security controls. D. Install and launch Jupyter Install the classroom packages python -m pip install --upgrade pippython -m pip install notebook jupyterlab numpy pandas matplotlib seaborn scipyjupyter notebook For JupyterLab, use jupyter lab. To finish, save files, stop the server with Ctrl+C, and run deactivate to leave the virtual environment. 8. Installing and using PyCharm PyCharm is a Python-focused IDE from JetBrains. Since PyCharm 2025.1, JetBrains provides one unified PyCharm product: essential core features remain free, while advanced Pro features require a subscription after the trial. Current official documentation states that core Jupyter support is included in the free functionality. Installation steps Step 1—Install Python first Use Python from python.org, Anaconda/conda, or allow PyCharm to create/select an interpreter during project setup. Step 2—Download PyCharm Visit https://www.jetbrains.com/pycharm/download/ and download the installer for Windows. Step 3 - Install Run the installer or use JetBrains Toolbox. Keep the default keymap unless you already use another one. Step 4 - Create a project Open PyCharm > New Project. Select a project folder and a Python interpreter. A project-specific virtual environment is good practice. Step 5 - Create a Python file Right-click the project folder > New > Python File. Name it first_bpharm_program.py. Step 6 - Run Enter the program and select the green Run button, or use the Windows shortcut Shift+F10 for the current run configuration. first_bpharm_program.py batch_number = "BPH-001"stock_units = 120print("Batch:", batch_number)print("Stock units:", stock_units) Interpreter check: If PyCharm underlines an installed package as missing, open Settings > Project > Python Interpreter and confirm that the project is using the same environment in which the package was installed. 9. Installing and using VS Code VS Code is a general-purpose code editor. For Python work, three separate pieces are required: VS Code, the Microsoft Python extension and a Python interpreter. The official VS Code documentation clearly states that the Python extension does not include Python itself. Installation steps Step 1 - Install Python Install Python from python.org or an approved conda distribution. Step 2 - Install VS Code Download it from https://code.visualstudio.com/download and complete the Windows installer. Step 3—Install the Python extension Open Extensions with Ctrl+Shift+X, search for Python by Microsoft and install it. Step 4—Install the Jupyter extension Install Jupyter by Microsoft if you will open or create .ipynb notebooks. Step 5—Open the course folder Select File > Open Folder and choose BPharm_Python. Step 6 - Select the interpreter Press Ctrl+Shift+P, choose Python: Select Interpreter and select the correct Python or course environment. Step 7 - Create and run a file Create first_bpharm_program.py, type the code, save it, and use the Run Python File play button. The integrated terminal can also run python first_bpharm_program.py. Terminal command to run a .py file python first_bpharm_program.py Opening a notebook in VS Code Create a file ending in .ipynb or open an existing notebook. Select the kernel shown near the upper-right area of the notebook editor. Choose the environment that contains the required packages. Use Shift+Enter to run a cell and move to the next cell. 10. Essential command reference CommandPurposepy --versionShow the Python version through the Windows launcher.python --versionShow the Python version for the active interpreter.python file_name.pyRun a Python script.python -m pip --versionShow pip linked to the active Python interpreter.python -m pip install package_nameInstall a package with pip.python -m pip install --upgrade package_nameUpgrade one package.python -m pip uninstall package_nameRemove one pip package after confirmation.python -m pip listList installed pip packages.python -m pip show pandasShow details and installation location of pandas.py -m venv bpharm_envCreate a virtual environment on Windows.bpharm_env\Scripts\activateActivate that environment in Windows Command Prompt.deactivateLeave a venv environment.conda --versionShow the conda version.conda create -n bpharm_python pythonCreate a conda environment.conda activate bpharm_pythonActivate a conda environment.conda deactivateLeave the active conda environment.conda listList packages in the active conda environment.conda install pandasInstall pandas through conda.conda remove pandasRemove pandas from the active conda environment.jupyter notebookStart Jupyter Notebook.jupyter labStart JupyterLab.jupyter --versionShow installed Jupyter component versions. Package rule for beginners: First activate the correct environment. Then install the package. Avoid mixing conda and pip randomly in the same environment. Prefer conda for packages available in the chosen conda channel; use pip when necessary and document what was installed. 11. Keyboard shortcuts Shortcuts may vary by operating system, keyboard layout, software version, and custom keymap. The tables below use common Windows defaults. Always open the program's Keyboard Shortcuts/Keymap screen when a shortcut behaves differently. Jupyter Notebook: two modes ModeHow to enterWhat the keyboard controlsEdit modeEnter or click inside a cellTyping and editing inside the selected cellCommand modeEsc or click outside the editing areaWhole-cell and notebook actions Common beginner error: Pressing A, B, M or D works as a notebook command only in Command mode. Press Esc first. ShortcutActionModeShift+EnterRun the cell and move to the next cellBoth / commonCtrl+EnterRun the cell and stay on itBoth / commonAlt+EnterRun the cell and insert a new cell belowBoth / commonCtrl+SSave the notebookBothEnterEnter Edit modeCommandEscEnter Command modeEditAInsert cell aboveCommandBInsert cell belowCommandMChange selected cell to MarkdownCommandYChange selected cell to CodeCommandC / X / VCopy / cut / paste selected cellCommandD, DDelete selected cell (press D twice)CommandZUndo cell deletionCommand1 to 6Change Markdown cell to heading level 1-6CommandLToggle line numbers for the selected cellCommandI, IInterrupt a busy kernelCommand0, 0Restart the kernelCommandHShow keyboard shortcutsCommandTabIndent or request completionEditShift+TabShow information/tooltip when availableEditCtrl+/Comment or uncomment selected codeEdit; version/keymap dependent PyCharm shortcuts (Windows default keymap) ShortcutActionShift+F10Run the current run configurationShift+F9Debug the current run configurationCtrl+Shift+F10Run the current context/fileCtrl+/Comment or uncomment selected linesCtrl+Alt+LReformat codeCtrl+SpaceCode completionAlt+EnterShow quick fix / intention actionDouble ShiftSearch everywhereCtrl+Shift+AFind an action by nameCtrl+Alt+SOpen Settings VS Code shortcuts (Windows) ShortcutActionCtrl+Shift+P or F1Open Command PaletteCtrl+Shift+XOpen ExtensionsCtrl+`Open or hide the integrated terminalCtrl+SSaveCtrl+/Comment or uncomment selected linesShift+Alt+FFormat the documentF5Start debuggingCtrl+F5Run without debugging when a suitable run action is configuredCtrl+K, Ctrl+SOpen Keyboard ShortcutsCtrl+PQuickly open a fileShift+EnterRun notebook cell and advance (in a notebook)Ctrl+EnterRun notebook cell and stay (in a notebook) IDLE shortcuts ShortcutActionF5Run Module (save the .py file first if prompted)Ctrl+SSaveCtrl+NNew fileCtrl+FFindCtrl+SpaceShow completion when available 12. Jupyter notebook operations students must know OperationWhat to doCreate a cellUse + / Insert, or press Esc then A (above) or B (below).Write codeSelect a Code cell, press Enter and type Python code.Write explanationPress Esc then M, type Markdown, and run the cell to format it.Run a cellPress Shift+Enter.SavePress Ctrl+S and confirm the notebook name.InterruptIf a cell never finishes, use Kernel > Interrupt or Esc then I, I.RestartUse Kernel > Restart when the variable state is confusing or the kernel fails.Run allAfter restart, use Run > Run All Cells to reproduce the notebook from the beginning.DownloadUse File > Save and Export/Download as available. Keep the original .ipynb file.Close safelySave, close/shut down the notebook, then stop the terminal server with Ctrl+C. Why restarting and running all cells is important Jupyter remembers variables created earlier in the current kernel. A notebook may appear to work even when cells were executed in a confusing order. Before submission, save the notebook, restart the kernel, and run all cells from top to bottom. If it still works, the notebook is more reproducible. Correct top-to-bottom order # Cell 1tablet_weight_mg = 500# Cell 2print(tablet_weight_mg) 13. Common errors and easy solutions ProblemLikely reasonSolution'python' is not recognizedPython is not on the command path, or the terminal was opened before installation.Open a new terminal; try py --version; repair/reinstall Python using the official installer if needed.'jupyter' is not recognizedJupyter is not installed in the active environment.Activate the correct environment; install notebook/jupyterlab; use Anaconda Prompt for Anaconda.ModuleNotFoundErrorThe package is missing from the interpreter/kernel currently running the code.Check the selected interpreter/kernel; install the package into that environment.Kernel keeps showing busyA cell may contain a long calculation or infinite loop.Use Interrupt. If necessary, restart the kernel, correct the code, and run again.NameErrorA variable name is misspelled or the cell that creates it was not run.Check spelling and execute cells from the beginning.IndentationErrorSpaces at the beginning of a line do not follow Python's block structure.Align lines carefully; use the editor's formatting/indent guides.No output appearsThe cell/file was not run, or the expression was assigned without print in a script.Run the cell/file; use print(...) when needed.Wrong package versionA different interpreter or environment is selected.Check python --version, package details and the IDE/kernel interpreter selector.Notebook opens in the wrong folderJupyter was started from another directory.Stop it, change directory with cd, and start jupyter notebook again.Browser page closedThe Jupyter server may still be running in the prompt.Use the URL displayed in the prompt, or stop and restart Jupyter safely. Safe diagnostic commands Windows Command Prompt / Anaconda Prompt where pythonwhere jupyterpython --versionpython -m pip --versionpython -m pip show pandas The where command shows which executable will run. If multiple paths are listed, the first one is normally used. Do not delete files from these locations blindly; select the correct interpreter or ask the lab administrator. 14. Practical Objective: Confirm that Python and the selected interface work by creating one Markdown explanation cell and three executable code cells. Part A - Create the notebook Open the BPharm_Python folder and start Jupyter Notebook. Create a Python 3 notebook. Rename it 02_IDE_Installation_Check.ipynb. Change the first cell to Markdown and type the title: # Python Installation Check. Run the Markdown cell with Shift+Enter. Part B - Execute the cells Cell 1 - Output test print("Python is working correctly.") Cell 2 - Store values medicine_name = "Paracetamol"batch_number = "BPH-001"stock_units = 120 Cell 3 - Display values print("Medicine:", medicine_name)print("Batch:", batch_number)print("Stock units:", stock_units) Part C—Verification checklist [ ] The notebook name is correct and ends in .ipynb. [ ] The Markdown heading is formatted, not shown with the # symbol after execution. [ ] All three code cells show a completed execution count. [ ] The output is correct, and no red error message is displayed. [ ] The notebook is saved. [ ] After Kernel Restart and Run All, the same output appears. 15. Quick revision QuestionAnswerIs Python an IDE?No. Python is a language and interpreter.Is Anaconda Navigator an IDE?No. It is a graphical launcher and environment/package interface.Is Jupyter Notebook a normal .py editor?It is primarily an interactive .ipynb notebook interface.Does the VS Code Python extension include Python?No. Install/select a Python interpreter separately.Which tool is recommended first for this course?Jupyter Notebook.Which is strongest for a structured Python-only project?PyCharm.Which is flexible for many languages?VS Code.What is the Jupyter kernel?The process that executes code and stores variables.What does Shift+Enter do?Runs the current notebook cell and advances.Why restart and run all?To prove that the notebook works in a clean, top-to-bottom order. 16. Glossary WordMeaningAutocompleteSuggestions that complete variable, function or file names while typing.BreakpointA marker that pauses a program during debugging.DebuggingFinding and correcting errors by examining the program's execution.ExtensionAn add-on that gives VS Code or another editor additional features.KernelThe process that runs notebook code.PATHA system list of folders searched when a command is typed.Package managerA tool such as pip or conda that installs and manages packages.Prompt / terminalA text window in which commands are typed.REPL / shellAn interactive place that reads one instruction, evaluates it and shows the result.Virtual environmentAn isolated Python setup for one project or course. 17. Final recommendation for the B.Pharm Python workshop StageUseReasonInitial classesJupyter NotebookBest for explanation, code, output and graphs in one teaching file.Data-analysis classesJupyterLab or Jupyter NotebookInteractive work with tables, statistics and plots.Programming projectsPyCharmStrong Python project organization and debugging.Mixed-technology projectsVS CodeSupports Python, notebooks, SQL, web files and many extensions.Very simple/offline fallbackIDLEInstalled with standard Python and suitable for tiny scripts. Teacher's one-line explanation: Python is the engine; Jupyter, PyCharm and VS Code are different dashboards used to control that engine. Official references Official documentation checked on 16 August 2026. Interfaces, shortcuts, versions and licensing can change, so use these links for the latest instructions. Python Software Foundation - Download Python: https://www.python.org/downloads/ Python documentation - IDLE: https://docs.python.org/3/library/idle.html Project Jupyter - Installing Jupyter: https://jupyter.org/install Jupyter Notebook documentation - Notebook Basics: https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/NotebookBasics.html Anaconda - Windows graphical installer: https://www.anaconda.com/docs/getting-started/anaconda/install/windows-gui-install Anaconda - Distribution download: https://www.anaconda.com/download JetBrains - Install PyCharm: https://www.jetbrains.com/help/pycharm/installation-guide.html JetBrains - Unified PyCharm overview: https://www.jetbrains.com/help/pycharm/unified-pycharm.html Microsoft - Getting Started with Python in VS Code: https://code.visualstudio.com/docs/python/python-tutorial Microsoft - VS Code keyboard shortcuts: https://code.visualstudio.com/docs/configure/keybindings Educational note: All medicine names, batch numbers, stock figures and strengths in these notes are simulated examples used only to teach programming. They are not clinical or dosing advice. Dr. Arpana Chaturvedi HOD-IT, Associate Professor (Department of IT and Data ANalytics, AI ML) New Delhi Institute of Management

Tag: Jupyter Notebook setup

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