- Professional Development
- Medicine & Nursing
- Arts & Crafts
- Health & Wellbeing
- Personal Development
The Land Manager Course gives you a clear and practical understanding of how to manage land in a smart and sustainable way. You will explore topics such as land use, soil care, irrigation, and land laws. This course teaches you how to make the most of land while protecting the environment and following legal rules. You will learn how to plan land use, control weeds, stop land damage, and manage water. The course also covers land rights, ownership, and how land is registered and transferred. Whether you're just starting out or want to improve your knowledge, this course gives you the tools to manage land responsibly. Course Curriculum ✓ Module 01: Land Management: An Introduction ✓ Module 02: Land Use and Land Use Planning ✓ Module 03: Soil Management ✓ Module 04: Land Degradation and Management ✓ Module 05: Weed Management ✓ Module 06: Watershed Management ✓ Module 07: Irrigation Management ✓ Module 08: Land Tenure, Administration and Transection ✓ Module 09: Land Registration and Acquisition ✓ Module 10: Land Law Learning Outcomes Understand the basics of land management. Learn how land is used and planned. Know how to manage and protect soil. Discover how to prevent and fix land damage. Learn ways to control weeds. Understand how to manage water and watersheds. Explore smart irrigation methods. Learn about land ownership and how land is handled. Understand the process of land registration and buying. Gain knowledge of UK land laws and how they affect land use. Who is this course for? This course is perfect for anyone interested in land care, farming, environmental work, or real estate. It suits students, landowners, developers, and professionals who want to learn how to manage land in a simple and clear way. Eligibility Requirements You don’t need any background in land or law to take this course. Anyone with an interest in the subject can enrol. A basic understanding of the environment or property is helpful but not needed. Career Path Completing this course opens doors to a variety of careers in land management. You can explore roles in local councils, real estate, farming, forestry, conservation, and land planning. It’s also a strong step towards advanced study or professional roles related to land use and development. (Learn more about this online course)
Level 1 Diploma in Gardening, Garden Design & Horticulture - CPD Certified
(1)By Empower UK Employment Training
Dive into the enriching world of Gardening and Horticulture. From landscaping design to hydroponics, plant nutrition, and pest management, this course offers comprehensive knowledge and practical skills. Unearth opportunities for a career in this green and growing field.
Hands-on Predicitive Analytics with Python (TTPS4879)
By Nexus Human
Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Hands-on Predicitive Analytics with Python (TTPS4879) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
