🎯 Key Takeaways for quick navigation: 00:08 *🚀 Introduction to Data Analytics* 02:40 *📊 Data Ecosystem and Sources* 07:25 *💡 Importance of Data for Business Decisions* 08:40 *🛠️ Roles in Data Analytics* 13:00 *📊 Types of Data Analysis* 18:48 *🗣️ Perspectives on Data Analytics* 22:00 *🎯 Responsibilities and Skills of Data Analysts* 26:43 *👩💼 Qualities and Skills for Data Analysts* 27:12 *📊 The importance of skills for data analysts* 31:22 *📈 A day in the life of a data analyst* 47:36 *📑 Overview of common data file formats* 52:23 *🌐 Common data sources for data analysts* 53:21 *📊 Data Sources for Analysis* 56:40 *🌐 APIs and Web Scraping for Data Collection* 58:54 *📈 Data Streams for Real-Time Analytics* 01:00:02 *💻 Overview of Data-Related Languages* 01:09:13 *🗄️ Overview of Data Repositories* 01:13:29 *🗃️ Relational Databases: Structure and Advantages* 01:28:42 *🏢 Data warehousing and ETL process* 01:40:48 *🛠️ Big Data analytics technologies* 01:45:49 *📊 Apache Spark for Data Processing* 01:47:17 *📝 Identifying Data for Use Cases* 01:50:01 *🔍 Ensuring Data Quality and Governance* 01:52:41 *📊 Understanding Data Sources* 02:10:58 *🛠️ Popular Data Wrangling Software and Tools* 02:11:12 *📊 Data Wrangling Tools Overview* 02:22:59 *🔍 Data Gathering and Preparation Importance* 02:27:05 *📊 Fundamentals of Statistical Analysis* 02:35:03 *🔍 Understanding Data Mining* 02:36:38 *📊 Data Mining Techniques and Applications* 02:40:31 *🛠️ Commonly Used Software and Tools for Data Mining* 02:46:31 *📈 Effective Communication of Data Analysis Results* 02:51:52 *📢 Role of Storytelling in Data Analysis* 02:54:55 *📊 Principles and Types of Data Visualization* 03:00:33 *🛠️ Data Visualization Software and Tools* 03:08:23 *💼 Data Analysts' Preferred Visualization Tools* 03:17:26 *🚀 Career Journeys of Data Professionals* 03:20:50 *🎯 Employer Expectations for Data Analysts* 03:24:28 *🧮 Skills Required for Data Analysts* 03:26:03 *🎓 Paths to Enter Data Analysis Field* 03:30:06 *🌐 Diverse Career Paths in Data Profession* 03:37:14 *👩💼 Women in Data Science* 03:40:23 *📊 Excel Data Analysis Course Overview* 03:47:51 *📊 Introduction to Spreadsheets and Basic Terminology* 03:54:29 *🖱️ Navigating a Spreadsheet and Understanding Ribbon and Menus* 04:06:50 *🔍 Data Entry, Viewing Features, and Data Editing* 04:09:43 *📊 Excel Data Entry and Editing* 04:12:36 *📋 Moving, Copying, and Filling Data* 04:16:27 *🖌️ Formatting Cells and Data* 04:20:16 *🧮 Introduction to Formulas* 04:27:10 *📊 Common and Advanced Functions* 04:57:16 *📊 Significance of Data Quality* 05:00:11 *🛡️ Importance of Data Privacy in Various Industries* 05:02:16 *🧹 Data Cleaning Techniques* 05:10:54 *🔄 Text Case Transformation and Date Formatting* 05:17:07 *🧹 Data Cleaning Techniques in Excel* 05:20:03 *🛠️ Excel Data Cleaning Tools: Flash Fill and Text to Columns* 05:26:12 *📊 Dealing with Poor Data Quality* 05:30:17 *🧮 Preparing Data for Analysis* 05:35:49 *🔍 Excel Data Filtering and Sorting* 05:39:07 *📊 Data Filtering and Sorting in Excel* 05:43:14 *🧮 Importance of Data Filtering and Sorting* 05:56:14 *📑 Excel Reference Functions: VLOOKUP and HLOOKUP* 06:02:05 *📊 Exploring HLOOKUP function in Excel* 06:06:14 *🔄 Utilizing Pivot Tables for Data Analysis* 06:14:04 *📊 Perspectives on Pivot Tables from Data Professionals* 06:17:27 *🔍 Exploring Advanced Pivot Table Features* 06:24:04 *📊 Excel Pivot Table Timelines* 06:39:16 *📊 Creating Basic Charts in Excel* 06:44:36 *📊 Creating Pivot Charts in Excel* 06:26:44 *📊 Recap: Pivot Table Features* 06:35:25 *🖼️ Importance of Visualizations - Expert Insights* 06:39:16 *📊 Creating Basic Charts in Excel - Line, Pie, Bar* 06:47:03 *📊 Excel Pivot Charts and Filtering* 06:50:43 *📈 Advanced Excel Charts* 06:58:35 *🗺️ Excel Filled Map Charts and Sparklines* 07:04:32 *📊 Introduction to Dashboards* 07:09:53 *📊 Importance of Effective Data Presentation* 07:12:08 *📊 Utilizing Cognos Analytics for Data Visualization* 07:14:12 *📊 Creating Dashboards in Excel* 07:21:35 *📊 Introduction to IBM Cognos Analytics* 07:31:40 *📊 Data Visualization in IBM Cognos Analytics* 07:35:04 *🐍 Python Data Types Overview* 07:38:00 *🧮 Python Expressions and Variables* 07:42:15 *🎻 String Operations in Python* 07:46:10 *📊 Lists and Tuples in Python* 07:54:55 *📚 Python Lists and Dictionaries* - Ordered collections with elements accessed by indices. - Elements can be modified, added, or removed. - Key-value pairs where values are accessed using keys. 07:57:12 *📊 Sets in Python* - No duplicate elements are allowed. 08:02:33 *🤔 Conditional Statements in Python* - Allow checking conditions like equality, inequality, greater than, less than, etc. - Enables running different code based on conditions using if, else, and elif statements. - Include `not`, `and`, and `or` to modify and combine Boolean values. - Useful for creating complex conditions and decision-making in code. 08:13:07 *🔄 Loops and Range Function in Python* - Generates sequences of numbers used in loops. - Can be customized to specify start, end, and step size. - For loops iterate over sequences like lists, executing a block of code for each element. - While loops execute a block of code as long as a condition is true. 08:14:38 *📊 Python Looping Techniques and Functions* 08:23:39 *📝 Advanced Function Concepts and Scopes* 08:39:36 *🔄 Python Objects and Classes Overview* 08:47:45 *📁 File Handling in Python* 08:54:33 *🐼 Introduction to Pandas Library* 08:57:29 *📊 Data Analysis Basics* 09:00:02 *🧮 Numpy Basics* 09:18:18 *🌐 Introduction to APIs* 09:18:50 *📊 Introduction to APIs and REST APIs* 09:23:38 *🎙️ Working with Watson APIs for Audio Transcription and Translation* 09:28:48 *🌐 Understanding HTTP Protocol and URL* 09:32:55 *📡 Working with HTTP Protocol in Python using Requests Library* 09:37:52 *🕸️ Understanding HTML for Web Scraping* 09:41:44 *🌐 Introduction to HTML and Web Scraping* 09:47:51 *📄 Working with Different File Formats* 09:51:58 *🖥️ HTML Review for Web Scraping* 09:57:02 *🕸️ Advanced Web Scraping with BeautifulSoup* 10:02:01 *📊 Importance of SQL in Data Science* 10:03:51 *📊 Introduction to SQL and Relational Databases* 10:12:33 *🎯 Useful Expressions in SELECT Statements* 10:17:38 *🔄 Updating and Deleting Data with UPDATE and DELETE Statements* 10:20:55 *🛢️ Database Concepts: Entity-Relationship Model and Data Types* 10:26:24 *☁️ Cloud Databases* 10:27:36 *🌐 Introduction to Cloud Databases* 10:32:31 *📊 Understanding SQL Statements* 10:35:01 *🔨 Creating Relational Database Tables* 10:47:31 *🔢 Sorting SELECT Statement Result Sets* 10:51:20 *📊 Working with SQL Queries: Eliminating Duplicates and Restricting Results* 10:54:09 *🛠️ Utilizing SQL Functions for Data Analysis* 11:00:18 *📅 Manipulating Date and Time Data in SQL* 11:03:11 *🔄 Mastering Subqueries in SQL* 11:14:47 *🐍 Accessing Databases Using Python* 11:28:22 *🗃️ Creating Tables, Loading Data, and Querying Data* 11:40:37 *📊 Exploratory Data Analysis with Box Plots* 11:48:43 *💼 Querying Data with Python* 11:50:35 *📊 Understanding Database Structure* 11:56:47 *📈 Exploring Data Sets and Libraries in Python* 12:01:55 *📊 Reading Data with Pandas* 12:04:26 *📊 Introduction to Pandas Data Exploration* 12:10:22 *🗃️ Accessing Databases with Python* 12:22:59 *🔄 Data Formatting and Conversion* 12:26:29 *📏 Data Normalization Techniques* 12:26:58 *📊 Normalizing Data:* 12:34:04 *📊 Exploratory Data Analysis (EDA) Basics:* 12:40:08 *🔄 Grouping Data:* 12:43:32 *📈 Correlation Analysis:* 12:49:11 *📊 Chi-Square Test for Independence* 12:53:45 *📈 Model Development Overview* 13:07:01 *🔄 Polynomial Regression and Pipelines* 13:11:29 *📉 Model Evaluation Metrics* 13:12:11 *📊 Understanding Mean Squared Error (MSE)* 13:21:11 *📊 Evaluating Model Generalization with Training and Testing Data* 13:33:24 *📈 Understanding Ridge Regression and Alpha Parameter* 13:42:08 *📊 Overview of Data Visualization with Python* 13:46:45 *📉 Importance of Effective Data Visualization* 13:58:09 *📊 Introduction to Matplotlib and Jupyter Notebook* 14:05:17 *📈 Line Plots: Visualization and Analysis* 14:08:56 *📉 Area Plots: Extending Line Plots* 14:13:45 *📊 Histograms: Analyzing Data Distributions* 14:18:41 *📊 Visualization with Matplotlib: Bar Chart* 14:22:12 *🥧 Visualization with Matplotlib: Pie Chart* 14:26:28 *📦 Visualization with Matplotlib: Box Plot* 14:30:32 *✳️ Visualization with Matplotlib: Scatter Plot* 14:36:26 *☁️ Advanced Visualization: Word Cloud* 14:40:23 *🌐 Advanced Visualization: Folium for Geographic Data* 14:41:31 *🗺️ Introduction to Folium and Map Creation* 14:43:08 *📍 Adding Markers to Maps* 14:45:12 *🌍 Understanding Choropleth Maps* 14:49:30 *📊 Importance of Interactive Data Applications* 14:54:24 *📈 Exploring Plotly Python Library* 14:57:23 *🔍 Analyzing Airline Reporting Data with Plotly* 14:58:13 *🖥️ Understanding Dash Library for Web Applications* Made with HARPA AI
@@Phronesis1037 I'm 100% sure channels also get income from Premium subscribers since we're paying for this service. Advertising isn't the only way to monetize.🤷♂️
@@JiMo711 TH-cam has been monitizing every channel since 2019. If you upload videos a couple of times, or get alot of views, then they automatically monetize you and take all the money.
Course#1 "What is Data Analytics" week 2 00:39:45 Overview of the Data Analyst Ecosystem 00:43:28 Types of Data 00:47:30 Understanding Different Types of File Formats 00:52:30 Sources of Data 01:00:25 Languages for Data Professionals 01:08:45 Overview of Data Repositories 01:13:20 RDBMS 01:20:55 NoSQL 01:28:30 Data Marts, Data Lakes, ETL, and Data Pipelines 01:35:15 Foundations of Big Data 01:40:38 Big Data Processing Tools
Good Morning, Please, can I have a copy of the course support (the diapositives) I am unable to download it from the links in the description box. Thanks.
Course#1 "What is Data Analytics" week 4 02:22:50 Data preparation and Reliability 02:34:55 What is Data Mining? 02:40:22 Tools for Data Mining 02:46:36 Overview of Communicating and Sharing Data Analysis Findings 02:51:40 Storytelling in Data Analysis 02:54:47 Introduction to Data Visualization 03:00:20 Introduction to Visualization and Dashboarding Software 03:08:03 Visualization Tools3мин
Course#1 "What is Data Analytics" week 3 01:47:05 Identifying Data for Analysis 01:52:35 Data Sources 01:57:20 How to Gather and Import Data 02:03:50 What is Data Wrangling? 02:10:50 Tools for Data Wrangling 02:16:25 Data Cleaning
Can i learn from the material here and just earn the certificate from coursera or do i have to enrol in the course on coursera first and then get a certificate?
Course#1 "What is Data Analytics" week 5 3:11:22 Career Opportunities in Data Analysis 3:17:24 Get into Data Profession 3:20:42 What do Employers look for in a Data Analyst? 3:25:50 The Many Paths to Data Analysis 3:29:51 Career Options for Data Professionals 3:33:20 Advice for aspiring Data Analysts 3:36:59 Women in Data Professions
Course#1 "What is Data Analytics" week 1 00:00:00 Course Introduction 00:02:45 Modern Data Ecosystem 00:07:30 Key Players in the Data Ecosystem 00:13:10 Defining Data Analysis 00:18:40 Viewpoints: What is Data Analytics? 00:21:50 Responsibilities of a Data Analyst 00:26:30 Qualities and Skills to be a Data Analyst 00:31:27 A Day in the Life of a Data Analyst 00:36:55 Applications of Data Analytics
The course is really great. It is very much helpful for those persons who want to make career in data analyst but are financially weak. Thanks for such a helpful video course.
This is great. Schooling us for FREE a coveted branch of IT Industry. I will never forget this generosity. Will definitely financially nurture this and the like projects once on my own feet.
I'm 38:08 minutes in and this video has been very helpful so far. I'm gearing up to take Data Management next semester. I feel confident I can master this subject with a little time. Thank you for making the subject plain/understandable.
5:45:00 IF Function 5:56:27 HLOOKUP and VLOOKUP 6:17:41 Pivot Tables 6:35:00 Line Charts, Pie Charts 6:51:00 Tree Maps, Scatter Charts, Histograms 6:58:00 Filled Map Charts, Sparklines 7:04:50 Dashboard
The first positive comment of the video out of 2. I hereby pledge to start and finish this course, plz hold me accountable. Start date: 19 Nov 2022 Completion date: 30 Jan 2023
I have completed the IBM data science and IBM Data Engineering courses on an e-learning learning platform (name withheld)...it didn't come cheap $$$. I must say a massive Thank You to this channel, it's not an easy feat. We appreciate your efforts.
Great upload! Thank you very much. For those who are whining about this video saying that you need to buy the full course to benefit from the certificate, I would say to them: Thank you mister obvious! These videos are great in preparing anyone to join the training and of course get the paid certificate since the training is based on a monthly fee. This means the more you get acquainted with the course and the exercises, the less time and money it will take you to get the certificate. And above all, be grateful to anyone who offers these great initiatives.
It is not true actually that you need to pay for the course in order to get the certificate. I did it without paying anything. There is a facility on the course page where you can apply for financing. I applied for financing for the whole set of courses up to certificate level (course completion) and was accepted on all courses. Hence, the certificate was free. Good luck.
@@promoteamutube hey man, does that mean that you apply for financing for each individual course (8 courses)? I apply for financing for the first one and I am still waiting for approval and it doesn’t allow me to submit my answer to the second quiz on the course unless I pay.
@@juanrosa6969 It is true that you can't submit your quiz answers until they reply. It took around 2 weeks for them to reply. You need to apply for each course and I did that all at the same time and got financed for all of them within 2 weeks.
Thank you so much for this video and the effort put into it. I have to submit my last assessment regarding the OOP topic in the next 2 weeks and this video is a "life-saver"!!!
Thank you very much for this course! It's hard to find any good course for money, but you made one for free. I can't even imagine how much effort you put into this video. THANK YOU
This is getting out of hands. You can get a full college education on youtube. You don't have to spend a dime. I was foolish not to have seen it earlier.
OmGod..i wanna be data analyst. And i started doing basics learning excel, sql ..but now i got this video....🤩🤩i will be learning from this video too from now wards 🥳 Thaankiyuuuuu somuchh ☺️☺️
Thank you so so much for sharing this training! In just first 15 minutes I had found clear answers to questions I had about modern data science sphere of knowledge.
Can we do data analytics after B.A. ? Because I'm confused some people say those who do this course who completed commerce or science stream..but I have humanities. So what should we do?
Good Accent English used, Generally Ameican accent is bit tough to catch by most of the students all over the globe. Hence this teacher gave in decent accent and maintained medium pace while giving lecture. Thank you very much my lesson for such a great video. Kudoos to you
Man..I'm currently enrolled in the Google Data Analytics course, and I always wondered about the IBM side.. How did this video happen.. I lost my words because the course is such valuable material and it's for free on TH-cam...
@@Kamcee_botanical I am about to finish it but it's not free, that being said it is only about $40 a month and you have access to not just the Data Analytics course but to a plethora of material and content. You can also cancel your subscription whenever you want to.
@@humayrahkhan7100 sorry for some reason I didn't see this comment. Honestly the Data Analytics certificate is pretty basic. I would recommend it to someone that has no background or wants to switch career paths and basically get their "feet wet". A bootcamp program at a university or getting an actual degree is the way to go. I am currently enrolled in a bootcamp program at the University and I can tell you I learned more in the first 2 weeks than the whole google certificate program.
5:57:35 small syntax error . Ive spent some time trying this without results , until i realized that the correct syntax is : =vlookup(b3;a2:b12;2;false) . ITS NOT SIMPLE COMMA . ( at least in my case , i see that in the tutorial it works with comma )
I'm here just to take a glance at the course, but on this matter, I want to inform you, that ; or , is based on a Locale (Regional) settings of the spreadsheet, which affects formatting details such as functions, dates, and currency. As per Google Sheets settings, and I believe, may affect the Excel too. Cheers
My The AllMugjty Good Lord Bless you and your family. Thasks for all your effort and dedication. He, Is The One you will receive your reward from. No doubt 🙏
Her definition of data scientist sounds a lot like what is being posted as the expected responsibilities of lower paid analysts out on the job boards. Anyone else noticing that?
Hi there! @32:38 welcome to visakhapatnam. I'm really sorry if mentioning the city name is inappropriate 'other than the content' in the comment section for this video. Because we don't have proper jobs here. Gratitude from Vishakapatnam.
Hats off to this channel! Can i know if this is all the video teaching materials for this course? I realised it is only a 15-hour long video but on the coursera site, it shows that 1 section is already 10+ hours, appreciate if someone can clear my doubts, thanks!
🎯 Key Takeaways for quick navigation:
00:08 *🚀 Introduction to Data Analytics*
02:40 *📊 Data Ecosystem and Sources*
07:25 *💡 Importance of Data for Business Decisions*
08:40 *🛠️ Roles in Data Analytics*
13:00 *📊 Types of Data Analysis*
18:48 *🗣️ Perspectives on Data Analytics*
22:00 *🎯 Responsibilities and Skills of Data Analysts*
26:43 *👩💼 Qualities and Skills for Data Analysts*
27:12 *📊 The importance of skills for data analysts*
31:22 *📈 A day in the life of a data analyst*
47:36 *📑 Overview of common data file formats*
52:23 *🌐 Common data sources for data analysts*
53:21 *📊 Data Sources for Analysis*
56:40 *🌐 APIs and Web Scraping for Data Collection*
58:54 *📈 Data Streams for Real-Time Analytics*
01:00:02 *💻 Overview of Data-Related Languages*
01:09:13 *🗄️ Overview of Data Repositories*
01:13:29 *🗃️ Relational Databases: Structure and Advantages*
01:28:42 *🏢 Data warehousing and ETL process*
01:40:48 *🛠️ Big Data analytics technologies*
01:45:49 *📊 Apache Spark for Data Processing*
01:47:17 *📝 Identifying Data for Use Cases*
01:50:01 *🔍 Ensuring Data Quality and Governance*
01:52:41 *📊 Understanding Data Sources*
02:10:58 *🛠️ Popular Data Wrangling Software and Tools*
02:11:12 *📊 Data Wrangling Tools Overview*
02:22:59 *🔍 Data Gathering and Preparation Importance*
02:27:05 *📊 Fundamentals of Statistical Analysis*
02:35:03 *🔍 Understanding Data Mining*
02:36:38 *📊 Data Mining Techniques and Applications*
02:40:31 *🛠️ Commonly Used Software and Tools for Data Mining*
02:46:31 *📈 Effective Communication of Data Analysis Results*
02:51:52 *📢 Role of Storytelling in Data Analysis*
02:54:55 *📊 Principles and Types of Data Visualization*
03:00:33 *🛠️ Data Visualization Software and Tools*
03:08:23 *💼 Data Analysts' Preferred Visualization Tools*
03:17:26 *🚀 Career Journeys of Data Professionals*
03:20:50 *🎯 Employer Expectations for Data Analysts*
03:24:28 *🧮 Skills Required for Data Analysts*
03:26:03 *🎓 Paths to Enter Data Analysis Field*
03:30:06 *🌐 Diverse Career Paths in Data Profession*
03:37:14 *👩💼 Women in Data Science*
03:40:23 *📊 Excel Data Analysis Course Overview*
03:47:51 *📊 Introduction to Spreadsheets and Basic Terminology*
03:54:29 *🖱️ Navigating a Spreadsheet and Understanding Ribbon and Menus*
04:06:50 *🔍 Data Entry, Viewing Features, and Data Editing*
04:09:43 *📊 Excel Data Entry and Editing*
04:12:36 *📋 Moving, Copying, and Filling Data*
04:16:27 *🖌️ Formatting Cells and Data*
04:20:16 *🧮 Introduction to Formulas*
04:27:10 *📊 Common and Advanced Functions*
04:57:16 *📊 Significance of Data Quality*
05:00:11 *🛡️ Importance of Data Privacy in Various Industries*
05:02:16 *🧹 Data Cleaning Techniques*
05:10:54 *🔄 Text Case Transformation and Date Formatting*
05:17:07 *🧹 Data Cleaning Techniques in Excel*
05:20:03 *🛠️ Excel Data Cleaning Tools: Flash Fill and Text to Columns*
05:26:12 *📊 Dealing with Poor Data Quality*
05:30:17 *🧮 Preparing Data for Analysis*
05:35:49 *🔍 Excel Data Filtering and Sorting*
05:39:07 *📊 Data Filtering and Sorting in Excel*
05:43:14 *🧮 Importance of Data Filtering and Sorting*
05:56:14 *📑 Excel Reference Functions: VLOOKUP and HLOOKUP*
06:02:05 *📊 Exploring HLOOKUP function in Excel*
06:06:14 *🔄 Utilizing Pivot Tables for Data Analysis*
06:14:04 *📊 Perspectives on Pivot Tables from Data Professionals*
06:17:27 *🔍 Exploring Advanced Pivot Table Features*
06:24:04 *📊 Excel Pivot Table Timelines*
06:39:16 *📊 Creating Basic Charts in Excel*
06:44:36 *📊 Creating Pivot Charts in Excel*
06:26:44 *📊 Recap: Pivot Table Features*
06:35:25 *🖼️ Importance of Visualizations - Expert Insights*
06:39:16 *📊 Creating Basic Charts in Excel - Line, Pie, Bar*
06:47:03 *📊 Excel Pivot Charts and Filtering*
06:50:43 *📈 Advanced Excel Charts*
06:58:35 *🗺️ Excel Filled Map Charts and Sparklines*
07:04:32 *📊 Introduction to Dashboards*
07:09:53 *📊 Importance of Effective Data Presentation*
07:12:08 *📊 Utilizing Cognos Analytics for Data Visualization*
07:14:12 *📊 Creating Dashboards in Excel*
07:21:35 *📊 Introduction to IBM Cognos Analytics*
07:31:40 *📊 Data Visualization in IBM Cognos Analytics*
07:35:04 *🐍 Python Data Types Overview*
07:38:00 *🧮 Python Expressions and Variables*
07:42:15 *🎻 String Operations in Python*
07:46:10 *📊 Lists and Tuples in Python*
07:54:55 *📚 Python Lists and Dictionaries*
- Ordered collections with elements accessed by indices.
- Elements can be modified, added, or removed.
- Key-value pairs where values are accessed using keys.
07:57:12 *📊 Sets in Python*
- No duplicate elements are allowed.
08:02:33 *🤔 Conditional Statements in Python*
- Allow checking conditions like equality, inequality, greater than, less than, etc.
- Enables running different code based on conditions using if, else, and elif statements.
- Include `not`, `and`, and `or` to modify and combine Boolean values.
- Useful for creating complex conditions and decision-making in code.
08:13:07 *🔄 Loops and Range Function in Python*
- Generates sequences of numbers used in loops.
- Can be customized to specify start, end, and step size.
- For loops iterate over sequences like lists, executing a block of code for each element.
- While loops execute a block of code as long as a condition is true.
08:14:38 *📊 Python Looping Techniques and Functions*
08:23:39 *📝 Advanced Function Concepts and Scopes*
08:39:36 *🔄 Python Objects and Classes Overview*
08:47:45 *📁 File Handling in Python*
08:54:33 *🐼 Introduction to Pandas Library*
08:57:29 *📊 Data Analysis Basics*
09:00:02 *🧮 Numpy Basics*
09:18:18 *🌐 Introduction to APIs*
09:18:50 *📊 Introduction to APIs and REST APIs*
09:23:38 *🎙️ Working with Watson APIs for Audio Transcription and Translation*
09:28:48 *🌐 Understanding HTTP Protocol and URL*
09:32:55 *📡 Working with HTTP Protocol in Python using Requests Library*
09:37:52 *🕸️ Understanding HTML for Web Scraping*
09:41:44 *🌐 Introduction to HTML and Web Scraping*
09:47:51 *📄 Working with Different File Formats*
09:51:58 *🖥️ HTML Review for Web Scraping*
09:57:02 *🕸️ Advanced Web Scraping with BeautifulSoup*
10:02:01 *📊 Importance of SQL in Data Science*
10:03:51 *📊 Introduction to SQL and Relational Databases*
10:12:33 *🎯 Useful Expressions in SELECT Statements*
10:17:38 *🔄 Updating and Deleting Data with UPDATE and DELETE Statements*
10:20:55 *🛢️ Database Concepts: Entity-Relationship Model and Data Types*
10:26:24 *☁️ Cloud Databases*
10:27:36 *🌐 Introduction to Cloud Databases*
10:32:31 *📊 Understanding SQL Statements*
10:35:01 *🔨 Creating Relational Database Tables*
10:47:31 *🔢 Sorting SELECT Statement Result Sets*
10:51:20 *📊 Working with SQL Queries: Eliminating Duplicates and Restricting Results*
10:54:09 *🛠️ Utilizing SQL Functions for Data Analysis*
11:00:18 *📅 Manipulating Date and Time Data in SQL*
11:03:11 *🔄 Mastering Subqueries in SQL*
11:14:47 *🐍 Accessing Databases Using Python*
11:28:22 *🗃️ Creating Tables, Loading Data, and Querying Data*
11:40:37 *📊 Exploratory Data Analysis with Box Plots*
11:48:43 *💼 Querying Data with Python*
11:50:35 *📊 Understanding Database Structure*
11:56:47 *📈 Exploring Data Sets and Libraries in Python*
12:01:55 *📊 Reading Data with Pandas*
12:04:26 *📊 Introduction to Pandas Data Exploration*
12:10:22 *🗃️ Accessing Databases with Python*
12:22:59 *🔄 Data Formatting and Conversion*
12:26:29 *📏 Data Normalization Techniques*
12:26:58 *📊 Normalizing Data:*
12:34:04 *📊 Exploratory Data Analysis (EDA) Basics:*
12:40:08 *🔄 Grouping Data:*
12:43:32 *📈 Correlation Analysis:*
12:49:11 *📊 Chi-Square Test for Independence*
12:53:45 *📈 Model Development Overview*
13:07:01 *🔄 Polynomial Regression and Pipelines*
13:11:29 *📉 Model Evaluation Metrics*
13:12:11 *📊 Understanding Mean Squared Error (MSE)*
13:21:11 *📊 Evaluating Model Generalization with Training and Testing Data*
13:33:24 *📈 Understanding Ridge Regression and Alpha Parameter*
13:42:08 *📊 Overview of Data Visualization with Python*
13:46:45 *📉 Importance of Effective Data Visualization*
13:58:09 *📊 Introduction to Matplotlib and Jupyter Notebook*
14:05:17 *📈 Line Plots: Visualization and Analysis*
14:08:56 *📉 Area Plots: Extending Line Plots*
14:13:45 *📊 Histograms: Analyzing Data Distributions*
14:18:41 *📊 Visualization with Matplotlib: Bar Chart*
14:22:12 *🥧 Visualization with Matplotlib: Pie Chart*
14:26:28 *📦 Visualization with Matplotlib: Box Plot*
14:30:32 *✳️ Visualization with Matplotlib: Scatter Plot*
14:36:26 *☁️ Advanced Visualization: Word Cloud*
14:40:23 *🌐 Advanced Visualization: Folium for Geographic Data*
14:41:31 *🗺️ Introduction to Folium and Map Creation*
14:43:08 *📍 Adding Markers to Maps*
14:45:12 *🌍 Understanding Choropleth Maps*
14:49:30 *📊 Importance of Interactive Data Applications*
14:54:24 *📈 Exploring Plotly Python Library*
14:57:23 *🔍 Analyzing Airline Reporting Data with Plotly*
14:58:13 *🖥️ Understanding Dash Library for Web Applications*
Made with HARPA AI
You made this list with HARPA AI?
😂😂😂😂😂at least AI!!! But human mind could trumble😮😮😮
Thank you. Road maps are so helpful. You are amazing.
Thank you
thank you. may you have a good place in heaven for this kindness.
I must sincerely say I have seen a good person who could put 15hours course for people without charging them. God bless you sir
Amen! Yes indeed God Bless this person!
The channel must have been already monetised by now, so they're making good profits, too.
@@JiMo711 this course is from coursera
@@Phronesis1037 I'm 100% sure channels also get income from Premium subscribers since we're paying for this service. Advertising isn't the only way to monetize.🤷♂️
@@JiMo711 TH-cam has been monitizing every channel since 2019. If you upload videos a couple of times, or get alot of views, then they automatically monetize you and take all the money.
Course#1 "What is Data Analytics" week 2
00:39:45 Overview of the Data Analyst Ecosystem
00:43:28 Types of Data
00:47:30 Understanding Different Types of File Formats
00:52:30 Sources of Data
01:00:25 Languages for Data Professionals
01:08:45 Overview of Data Repositories
01:13:20 RDBMS
01:20:55 NoSQL
01:28:30 Data Marts, Data Lakes, ETL, and Data Pipelines
01:35:15 Foundations of Big Data
01:40:38 Big Data Processing Tools
Good Morning,
Please, can I have a copy of the course support (the diapositives)
I am unable to download it from the links in the description box.
Thanks.
Thank you
Course#1 "What is Data Analytics" week 4
02:22:50 Data preparation and Reliability
02:34:55 What is Data Mining?
02:40:22 Tools for Data Mining
02:46:36 Overview of Communicating and Sharing Data Analysis Findings
02:51:40 Storytelling in Data Analysis
02:54:47 Introduction to Data Visualization
03:00:20 Introduction to Visualization and Dashboarding Software
03:08:03 Visualization Tools3мин
Course#1 "What is Data Analytics" week 3
01:47:05 Identifying Data for Analysis
01:52:35 Data Sources
01:57:20 How to Gather and Import Data
02:03:50 What is Data Wrangling?
02:10:50 Tools for Data Wrangling
02:16:25 Data Cleaning
Can i learn from the material here and just earn the certificate from coursera or do i have to enrol in the course on coursera first and then get a certificate?
Course#1 "What is Data Analytics" week 5
3:11:22 Career Opportunities in Data Analysis
3:17:24 Get into Data Profession
3:20:42 What do Employers look for in a Data Analyst?
3:25:50 The Many Paths to Data Analysis
3:29:51 Career Options for Data Professionals
3:33:20 Advice for aspiring Data Analysts
3:36:59 Women in Data Professions
Course#1 "What is Data Analytics" week 1
00:00:00 Course Introduction
00:02:45 Modern Data Ecosystem
00:07:30 Key Players in the Data Ecosystem
00:13:10 Defining Data Analysis
00:18:40 Viewpoints: What is Data Analytics?
00:21:50 Responsibilities of a Data Analyst
00:26:30 Qualities and Skills to be a Data Analyst
00:31:27 A Day in the Life of a Data Analyst
00:36:55 Applications of Data Analytics
Thanks this helps a lot
thank you
You are my hero! Thank you so much for the time codes!!!
The course is really great. It is very much helpful for those persons who want to make career in data analyst but are financially weak. Thanks for such a helpful video course.
Buddy could u help me to find the right path for di
This is great. Schooling us for FREE a
coveted branch of IT Industry. I will never forget this generosity. Will definitely financially nurture this and the like projects once on my own feet.
Is this particular course outdated?
I'm 38:08 minutes in and this video has been very helpful so far. I'm gearing up to take Data Management next semester. I feel confident I can master this subject with a little time. Thank you for making the subject plain/understandable.
5:45:00 IF Function
5:56:27 HLOOKUP and VLOOKUP
6:17:41 Pivot Tables
6:35:00 Line Charts, Pie Charts
6:51:00 Tree Maps, Scatter Charts, Histograms
6:58:00 Filled Map Charts, Sparklines
7:04:50 Dashboard
The first positive comment of the video out of 2.
I hereby pledge to start and finish this course, plz hold me accountable.
Start date: 19 Nov 2022
Completion date: 30 Jan 2023
Update?
Is it helpful?
Update????
Update?!!!
Did it work?
This is the full ibm data analytics in coursera 😁
Thanks 👍
is it worth it to do?
hands down one of my most fav tech learning channel
I have completed the IBM data science and IBM Data Engineering courses on an e-learning learning platform (name withheld)...it didn't come cheap $$$. I must say a massive Thank You to this channel, it's not an easy feat. We appreciate your efforts.
Coursera or edX
Just audit the course for free no?
Did you get a data analyst job?
1 lakh course fee
Name withheld? You must be selling eja
Great upload! Thank you very much.
For those who are whining about this video saying that you need to buy the full course to benefit from the certificate, I would say to them: Thank you mister obvious!
These videos are great in preparing anyone to join the training and of course get the paid certificate since the training is based on a monthly fee. This means the more you get acquainted with the course and the exercises, the less time and money it will take you to get the certificate.
And above all, be grateful to anyone who offers these great initiatives.
It is not true actually that you need to pay for the course in order to get the certificate. I did it without paying anything. There is a facility on the course page where you can apply for financing. I applied for financing for the whole set of courses up to certificate level (course completion) and was accepted on all courses. Hence, the certificate was free. Good luck.
@@promoteamutube hey man, does that mean that you apply for financing for each individual course (8 courses)? I apply for financing for the first one and I am still waiting for approval and it doesn’t allow me to submit my answer to the second quiz on the course unless I pay.
@@juanrosa6969 It is true that you can't submit your quiz answers until they reply. It took around 2 weeks for them to reply. You need to apply for each course and I did that all at the same time and got financed for all of them within 2 weeks.
You can audit all of the courses for free
@@daextraxtor681 Can you take the quizzes and submit assignments on audit mode?
a Deep Deep heartfelt gratitude for putting in all this work and sharing it with us for no compensation. God Truly Truly Bless You!
I am from a 3rd tier state of indian, and i am greatful to this courses because i am learning it free of course.God bless you
Thank you so much for this video and the effort put into it. I have to submit my last assessment regarding the OOP topic in the next 2 weeks and this video is a "life-saver"!!!
How did ur assignment go? Are u working as a data analyst now? Good luck
Thank you very much for this course! It's hard to find any good course for money, but you made one for free. I can't even imagine how much effort you put into this video.
THANK YOU
This is getting out of hands. You can get a full college education on youtube. You don't have to spend a dime. I was foolish not to have seen it earlier.
7:07:46 Advanced Data Analysis and Visualization apps
7:15:26 Excel Dashboard
7:21:53 Cognos Analytics
7:35:04 Python
THIS IS AWESOME.I REALLY APPRECIATE YOU FOR MAKING THIS COURSE FREE OF CHARGE.
Love from India. I appreciate the good heart and effort of the person in uploading the video. Keep sharing the knowledge.
Hi I am from India... did.u get job after this course completion?
God bless your soul, I wish you everything best in this life, thank you
OmGod..i wanna be data analyst. And i started doing basics learning excel, sql ..but now i got this video....🤩🤩i will be learning from this video too from now wards 🥳 Thaankiyuuuuu somuchh ☺️☺️
Hi I have zero knowledge of data analysis. Is this video helpful?? How was your experience till now
Hey 👋🏻
Have you been to some company yet
Am about to start this. Excited.
Thank you so so much for sharing this training! In just first 15 minutes I had found clear answers to questions I had about modern data science sphere of knowledge.
You mean 15hours?
Can we do data analytics after B.A. ? Because I'm confused some people say those who do this course who completed commerce or science stream..but I have humanities. So what should we do?
@@ewuolakabir3989 minutes. I had found answers to some questions, not all of them. :) I still meed to finish watching.
@@babitakumari2131 Absolutely. Any kind of data could and should be analysed.
@@СашиныРазговорчики have you done this course?
I absolutely love this course. Thank you, thank you, and thank you!!!
Deepest thanks for being a Godsend blessing! Keep up the great work!
Good Accent English used, Generally Ameican accent is bit tough to catch by most of the students all over the globe. Hence this teacher gave in decent accent and maintained medium pace while giving lecture. Thank you very much my lesson for such a great video. Kudoos to you
No American accent is the easiest to catch.
American English is the easiest dialect to understand. Better than a thick Indian accent.
Thank you so much for the detailed full course. God bless you abundantly. May you never lack in times of need👏🏾👏🏾🙏🏾
Thank you! You too!
This is a Miracle. Angel deed by putting out this course for free. Thanks a Billion. Blessed!.
Thanks a lot for free course I want restart my career it is god had send me this video thanks a lot from heart
is it certified course??
I'm so grateful for this. I am going to really apply myself to this.
did you?
Really appreciating the efforts to share the knowledge and Content👏👏.. As a beginner for me this video worth to watch
09:18:20 API to 9:51:59 Webscraping
Man..I'm currently enrolled in the Google Data Analytics course, and I always wondered about the IBM side.. How did this video happen.. I lost my words because the course is such valuable material and it's for free on TH-cam...
Greetings to you, please I would like to know if the course on Google is free.
@@Kamcee_botanical I am about to finish it but it's not free, that being said it is only about $40 a month and you have access to not just the Data Analytics course but to a plethora of material and content. You can also cancel your subscription whenever you want to.
@@MrToco23 so what's your opinion on Google or IBM please reply... which course is best
@@humayrahkhan7100 sorry for some reason I didn't see this comment. Honestly the Data Analytics certificate is pretty basic. I would recommend it to someone that has no background or wants to switch career paths and basically get their "feet wet". A bootcamp program at a university or getting an actual degree is the way to go. I am currently enrolled in a bootcamp program at the University and I can tell you I learned more in the first 2 weeks than the whole google certificate program.
How do I apply for a data analyst job
Thank you So much. God bless you abundantly. You didn't know how great this help is
Complete the video before IBM Sue this channel ❤❤❤🎉🎉🎉
He put all of them in one video. Nice!!
Is this the complete version of IBM 40-hour long courses? How he condense the courses into just 15 hours?
this course help me most. Thanku you
This amazing omg thanks thanks thanks. I can see that it answer literaly all my question just from checking the rode map.
any comments about too much commercials because of thie free knowledge instruction😎?
Thank you for this wonderful opportunity to have access to this course all for free. God bless you
i am foreigner so the subtitle help me a lot to understand cause less video outthere have subtitles.
I love you so much, Thanks a ton for this wonderful video and knowledge sharing. Please keep doing your Nobel service
Amazing endowment to us, a good contribution to those who need as myself is.
Python 7:35:12 🎉
Great content but wow! Never seen so many ads in a single video
This! I appreciate the generosity and certainly wouldn’t mind an ad or two but every 5 min??!!! Nope, I’ll get the info elsewhere.
What a informative video. Thanks for detailed course.
😮 This is GOLD! Thanks!
Thank you so much for this resource. Very insightful
Thank you for sharing such a knowledgeable information
Thank you, I am blessed by your work. God bless you😄
Thank you for sharing this information to the entire world kudoo
Good bless you sir respect by heart 🙏
6:14:13 pivot tables
Thank you so much for this informative starter. Bless you❤
I would like to watch a video of everything about "Computer Science" made by you
Thank you so much for this video.
It helped me a lot.
Thanku soo much very need full video ❤️
5:57:35 small syntax error . Ive spent some time trying this without results , until i realized that the correct syntax is : =vlookup(b3;a2:b12;2;false) . ITS NOT SIMPLE COMMA . ( at least in my case , i see that in the tutorial it works with comma )
I'm here just to take a glance at the course, but on this matter, I want to inform you, that ; or , is based on a Locale (Regional) settings of the spreadsheet, which affects formatting details such as functions, dates, and currency. As per Google Sheets settings, and I believe, may affect the Excel too. Cheers
God bless you for this course
This is helpful for learning data analytics
Thanks by sharing this knowledge with community
Well detailed lecture, Thanks 🙏
Hello, My Lesson.
This study material Link doesn't have the Excel files for the practice, Do you have any other link to get them?
unparalleled generosity .
Thanks for time stamp
I'm starting this today.
How's it going
Excellent!! Thank you.
This is exactly what we are doing for work, and we do this just two person only
I'm excited to have learned a whole lot
Thanks, I'll watch the full video...
Thank you, appreciate!
I'm about to start the 15hrs journey. Please quick question, does the course explore the use of KPI ?
wow! salamat po from the Philippines! ☺
Hello po beginner din kayo sa DA?
Sino po pede maging study buddy for DA?
Thank you so much for this course, may God bless you. could you please share the data used so that we can have some data to learn with
Thank you so much, it was so valuable
Very very nice🎉🎉
My The AllMugjty Good Lord Bless you and your family. Thasks for all your effort and dedication. He, Is The One you will receive your reward from. No doubt 🙏
I think you need to add an ''intro'' to timestamps to make it work
thanks for this awesome video!!!
Her definition of data scientist sounds a lot like what is being posted as the expected responsibilities of lower paid analysts out on the job boards. Anyone else noticing that?
Thank you a lot for this work ❤
God bless you sir
Thanks a lot for this resources.
God bless you real good
Thanks alot for this package
I really love this
Please sir can I get data engineering course too??
Python 7:21:00
The business speak in this video is second to none. It's like they get paid per word in business speak.
Thank you so much.❤
Hi there! @32:38 welcome to visakhapatnam.
I'm really sorry if mentioning the city name is inappropriate 'other than the content' in the comment section for this video. Because we don't have proper jobs here.
Gratitude from Vishakapatnam.
can you upload full cyber security course for beginner with python used in cyber security
Hats off to this channel!
Can i know if this is all the video teaching materials for this course? I realised it is only a 15-hour long video but on the coursera site, it shows that 1 section is already 10+ hours, appreciate if someone can clear my doubts, thanks!
coursera will have assignments also
wow so much interesting
Thank you sir !!!
What are the differences between this course and the data engineering by Meta course mentioned above?