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Establishing a Business Analysis Framework to Increase Organizational Agility Establishing a Business Analysis Framework to Increase Organizational Agility In managing today's complex project portfolios, many organizations are faced with challenges due to globalization, changing business priorities, and technological demands. To respond quickly to these challenges, organizations have to embrace change in order to become more agile. Business analysis is a critical element to achieving this organizational agility. More importantly, establishing an effective business analysis framework ensures that an organization can repeatedly deliver solutions that are aligned to goals and objectives that may evolve over time. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00

Are you looking to enhance your Data Analysis with Excel skills? If yes, then you have come to the right place. Our comprehensive course on Data Analysis with Excel will assist you in producing the best possible outcome by mastering the Data Analysis with Excel skills. The Data Analysis with Excel is for those who want to be successful. In the Data Analysis with Excel, you will learn the essential knowledge needed to become well versed in Data Analysis with Excel. Our Data Analysis with Excel starts with the basics of Data Analysis with Excel and gradually progresses towards advanced topics. Therefore, each lesson of this Data Analysis with Excel is intuitive and easy to understand. Why would you choose the Data Analysis with Excel from Compliance Central: Lifetime access to Data Analysis with Excel materials Full tutor support is available from Monday to Friday with the Data Analysis with Excel Learn Data Analysis with Excel skills at your own pace from the comfort of your home Gain a complete understanding of Data Analysis with Excel Accessible, informative Data Analysis with Excel learning modules designed by expert instructors Get 24/7 help or advice from our email and live chat teams with the Data Analysis with Excel bundle Study Data Analysis with Excel in your own time through your computer, tablet or mobile device. A 100% learning satisfaction guarantee with your Data Analysis with Excel Improve your chance of gaining in demand skills and better earning potential by completing the Data Analysis with Excel Data Analysis with Excel Curriculum Breakdown of the Data Analysis with Excel Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows Search for and Replace Data Use Proofing and Research Tools Working with Lists Sort Data Filter Data Query Data with Database Functions Outline and Subtotal Data Analyzing Data Apply Intermediate Conditional Formatting Apply Advanced Conditional Formatting Visualizing Data with Charts Create Charts Modify and Format Charts Use Advanced Chart Features Using PivotTables and PivotCharts Create a PivotTable Analyze PivotTable Data Present Data with PivotCharts Filter Data by Using Timelines and Slicers Working with Multiple Worksheets and Workbooks Use Links and External References Use 3-D References Consolidate Data Using Lookup Functions and Formula Auditing Use Lookup Functions Trace Cells Watch and Evaluate Formulas Automating Workbook Functionality Apply Data Validation Search for Invalid Data and Formulas with Errors Work with Macros Creating Sparklines and Mapping Data Create Sparklines MapData Forecasting Data Determine Potential Outcomes Using Data Tables Determine Potential Outcomes Using Scenarios Use the Goal Seek Feature Forecasting Data Trends CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Data Analysis with Excel helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Data Analysis with Excel. It is also great for professionals who are already working in Data Analysis with Excel and want to get promoted at work. Requirements To enrol in this Data Analysis with Excel, all you need is a basic understanding of the English Language and an internet connection. Career path The Data Analysis with Excel will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Data Analysis with Excel. Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99

Join our Business Management Diploma course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Business Management Diploma course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Business Management Diploma course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! You will Learn The Following Things: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Business Management Diploma. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-to-one support from a dedicated tutor throughout your course. Study online - whenever and wherever you want. Instant Digital/ PDF certificate 100% money back guarantee 12 months access Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital/PDF Certificate After completing the Business Management Diploma course, you can order your CPD-accredited Digital/PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. (Each) Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Business Management Diploma is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the Business Management Diploma course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Business Management Diploma Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Module 01: Introduction to Business Management Introduction to Business Management 00:25:00 Module 02: Operations Management Operations Management 00:24:00 Module 03: Introduction to Business Analysis Introduction to Business Analysis 00:14:00 Module 04: Strategic Analysis and Product Scope Strategic Analysis and Product Scope 00:28:00 Module 05: Project Management Project Management 00:19:00 Module 06: Business Development and Succession Planning Business Development and Succession Planning 00:24:00 Module 07- Business Process Management Business Process Management 00:44:00 Module 08: Planning & Forecasting Operations Planning & Forecasting Operations 00:21:00 Module 09: Performance Management Performance Management 00:18:00 Module 10: Management of Cash and Credit Management of Cash and Credit 00:19:00 Module 11: Managing Risk and Recovery Managing Risk and Recovery 00:26:00 Module 12: Quality Management Quality Management 00:21:00 Module 13: Communication Skills Communication Skills 00:25:00 Module 14: Business Environment Business Environment 00:16:00 Module 15: Organisational Skills Organisational Skills 01:16:00 Module 16: Negotiation Techniques Negotiation Techniques 00:16:00 Module 17: Human Resource Management Human Resource Management 00:19:00 Module 18: Motivation and Counselling Motivation and Counselling 00:19:00 Module 19: Customer Service Customer Service 00:16:00 Module 20: Time Management Time Management 00:40:00 Module 21: Conflict Management Conflict Management 00:14:00 Assignment Assignment - Business Management 00:00:00

Are you looking to enhance your Agile skills? If yes, then you have come to the right place. Our comprehensive course on Agile will assist you in producing the best possible outcome by mastering the Agile skills. The Agile course is for those who want to be successful. In the Agile course, you will learn the essential knowledge needed to become well versed in . Our Agile course starts with the basics of Agile and gradually progresses towards advanced topics. Therefore, each lesson of this Agile course is intuitive and easy to understand. Why would you choose the Agile course from Compliance Central: Lifetime access to Agile course materials Full tutor support is available from Monday to Friday with the Agile course Learn Agile skills at your own pace from the comfort of your home Gain a complete understanding of Agile course Accessible, informative Agile learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Study Agile in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Agile course Learn at your own pace from the comfort of your home, as the rich learning materials of this course are accessible from any place at any time. The curriculums are divided into tiny bite-sized modules by industry specialists. And you will get answers to all your queries from our experts. Learning Outcomes of the Agile Course: Comprehend objectives and targets in the legal profession. Transition from traditional models to agile development. Update knowledge with the 2020 Scrum Guide changes. Understand Scrum, its team structure, events, and artefacts. Learn techniques to scale Scrum in diverse environments. Prepare effectively for PSM1 certification with guided tips. So, enrol and excel in your career with Compliance Central. Course Certificate of Achievement After successfully completing this course, you will get an instant PDF certificate from Reed for free. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Agile course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in . It is also great for professionals who are already working in Agile and want to get promoted at work. Requirements To enrol in this Agile course, all you need is a basic understanding of the English Language and an internet connection. Career path The Agile course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to: Agile Project Manager - £40-60k/year Scrum Master - £45-70k/year Legal Consultant (Agile Implementation) - £50-75k/year Legal Process Manager - £35-55k/year PSM1 Certified Paralegal - £30-45k/year Certificates Reed courses certificate of completion Digital certificate - Included Will be downloadable when all lectures have been completed CPD Quality Standard Certificate Digital certificate - £7.99

About Course Data Science and Data Analytics with Python: A Comprehensive Course for Beginners Unlock the power of data and gain insights that drive informed decisions with this comprehensive course on data science and data analytics with Python. This course is designed for beginners of all skill levels, with no prior programming experience required. You will learn the essential skills to embark on your data-driven journey, including: Data manipulation with NumPy and Pandas Data visualization with Matplotlib and Seaborn Statistical analysis with Python Machine learning and artificial intelligence You will also gain hands-on experience with real-world data projects, allowing you to apply your newfound knowledge to solve real-world problems. By the end of this course, you will be able to: Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems This course is the perfect launchpad for your data science journey. Whether you are looking to pivot your career, enhance your skill set, or simply quench your curiosity, this course will give you the foundation you need to succeed. Enroll today and start exploring the fascinating world of data science together! What Will You Learn? Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems Course Content Introduction to Python Data Science Introduction to Python Data Science Environment Setup Data Cleaning Packages Working with the Numpy package Working with Pandas Data science package Data Visualization Packages Working with Matplotlib Data Science package (Part - 1) Working with Matplotlib Data Science (Part - 2) A course by Uditha Bandara Microsoft Most Valuable Professional (MVP) RequirementsBeginners level knowledge for working with Data .Programming knowledge not required. Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics

Personal Agility: Being Agile Starts with You The emphasis of agile has always been on the power of the team and the agility of the organization. However, we have skipped one important part: YOU as an individual! Being agile isn't about the processes or practices (we are just doing agile at that point) but about the shift needed in culture and mindset. The only way to change the culture is to take a human-centered approach by starting with ourselves first to understand our current beliefs and biases. During this session, participants will explore through a series of exercises how they currently embody the agile values and principles and where they struggle. Understand your own personal agility Understand the impact your agility has on how you operate within your teams and your organization Gain some new tools to support others in discovering their own personal agility and self-reflection

Personal Agility: Being Agile Starts with You The emphasis of agile has always been on the power of the team and the agility of the organization. However, we have skipped one important part: YOU as an individual! Being agile isn't about the processes or practices (we are just doing agile at that point) but about the shift needed in culture and mindset. The only way to change the culture is to take a human-centered approach by starting with ourselves first to understand our current beliefs and biases. During this session, participants will explore through a series of exercises how they currently embody the agile values and principles and where they struggle. Understand your own personal agility Understand the impact your agility has on how you operate within your teams and your organization Gain some new tools to support others in discovering their own personal agility and self-reflection

Agile Economics for Better Customer Experience & Faster Business Value Realization With disruptive technology advances, software assets play an increasingly important role in creating a competitive advantage for organizations. In order to keep up the speed to market, businesses turn agile methods to deliver better customer experience and faster business value realization.This presentation will be focused on the benefits of agile economics and explain how to appropriately select the best budgeting model and how to interpret and apply accepted accounting standards as SOP 98-1 for internal software development to more effectively adopt and transform agile at any organization. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.