587 Machine Learning (ML) courses

Ever wondered how machines recognise faces, detect traffic signs, or even tag photos with uncanny accuracy? This course dives straight into the heart of Convolutional Neural Networks (CNNs) – the very engine behind image recognition and deep learning breakthroughs. With a clear focus on project-based learning, you’ll explore how CNNs work, how they’re built, and how they’re trained to see and interpret the world digitally. The content flows logically and stays rooted in clarity, making even the most complex architectures feel almost polite. This is not just a sequence of slides and jargon. It’s a well-structured digital journey tailored for learners who want to confidently grasp how deep learning models behave and evolve. Whether you're brushing up on your neural network knowledge or aiming to reinforce your AI expertise, the course serves up algorithms, code walkthroughs and layered insights with a tone that’s informative, direct, and occasionally dry-witted. If you fancy turning raw data into pixel-level predictions using nothing but code, logic, and neural layers — you’re exactly where you need to be. Learning Outcomes: Gain a solid understanding of convolutional neural networks and their applications in deep learning. Learn how to install the necessary packages and set up a dataset structure for deep learning projects. Discover how to create your own convolutional neural network model and layers using Python. Understand how to preprocess and augment data for advanced image recognition tasks. Learn how to evaluate the accuracy of your models and understand the different models available for deep learning projects. The Deep Learning Projects - Convolutional Neural Network course is designed to provide you with the skills and knowledge you need to build your own advanced deep learning projects. Using Python, you'll learn how to install the necessary packages, set up a dataset structure, and create your own convolutional neural network model and layers. You'll also learn how to preprocess and augment data to enhance the accuracy of your models and evaluate the performance of your models using data generators. Deep Learning Projects - Convolutional Neural Network Course Curriculum Section 01: Introduction Section 02: Installations Section 03: Getting Started Section 04: Accuracy How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data analysts who want to expand their skills in deep learning and convolutional neural networks. Programmers who want to learn how to build advanced models for image recognition. Entrepreneurs who want to develop their own deep learning-based applications for image recognition. Students who want to enhance their skills in deep learning and prepare for a career in the field. Anyone who wants to explore the world of convolutional neural networks and deep learning projects. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Computer Vision Engineer: £30,000 - £70,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Ever wondered how to speak confidently about buildings, materials, and construction terms—in Portuguese? This course is your blueprint to building language skills tailored to the world of structural design and architecture. From concrete columns to roofing terms, you'll learn how to talk structures with precision and clarity—all in Portuguese. Whether you're a construction enthusiast, a professional working with Portuguese-speaking clients, or simply keen to expand your vocabulary, this course is structured to help you build fluency without ever picking up a hammer. Expect engaging modules that introduce you to the foundations of structural language—from everyday construction phrases to technical expressions. It's not about laying bricks; it's about laying down words that matter. Delivered entirely online, this course offers you the flexibility to learn from wherever you are, while gaining knowledge that’s both specific and linguistically sharp. If structure speaks to you, let it speak Portuguese too. Learning Outcomes: Gain a solid understanding of artificial neural networks and their applications in deep learning. Learn how to install the necessary packages and preprocess data for neural network training. Discover how to encode data and build your own artificial neural network using Python. Understand the steps involved in making predictions using your neural network model. Learn how to deal with imbalanced data in your neural network training. The Project on Deep Learning - Artificial Neural Network course is designed to provide you with the skills and knowledge you need to build your own neural network and perform complex tasks using deep learning. You'll learn how to install the necessary packages, preprocess data, and encode data for neural network training. You'll also gain a deeper understanding of artificial neural networks and learn how to build your own model using Python. By the end of the course, you'll be able to make predictions using your neural network model and understand how to deal with imbalanced data in your training. Build Structures in Portuguese Course Curriculum Introduction Section 01: Chapter 1 Section 02: Chapter 2 Section 03: Chapter 3 Section 04: Chapter 4 Section 05: Chapter 5 Section 06: Chapter 6 Section 07: Chapter 7 Section 08: Chapter 8 Section 09: Chapter 9 Section 10: Chapter 10 How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data analysts who want to expand their skills in deep learning and artificial neural networks. Programmers who want to learn how to build their own neural network models for advanced tasks. Entrepreneurs who want to develop their own deep learning-based applications. Students who want to enhance their skills in deep learning and prepare for a career in the field. Anyone who wants to explore the world of artificial neural networks and deep learning projects. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Deep Learning Engineer: £30,000 - £75,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Python isn’t just a programming language—it’s the secret weapon behind automation, web development, data analysis, and more. Whether you're aiming to write clean, efficient code or understand how modern applications are built, this course brings the full Python ecosystem to your screen. With a clear, structured journey from the absolute basics to more advanced topics, this masterclass helps you grasp key programming concepts without fluff or filler. Forget drawn-out tech jargon. This course makes coding feel less like solving a mystery and more like connecting the dots. From syntax and loops to functions and object-oriented techniques, each topic is delivered with clarity, a hint of humour, and the kind of logic Python is famous for. Whether you’re starting fresh or polishing old skills, this course offers a solid digital foundation that’s accessible, flexible, and thoroughly built for modern learners who want Python done right. Learning Outcomes: Understand the fundamentals of Python programming and its applications in various industries. Analyse and manipulate data using lists, tuples, strings, and dictionaries in Python. Develop programming solutions using Python's standard libraries and reference files. Create and implement control flow structures using conditions, loops, and statements. Utilise advanced features of Python such as magic methods, properties, and iterators. "Ultimate Python Programming Masterclass" is a comprehensive course bundle designed to equip learners with the knowledge and skills necessary to master Python programming. This course covers a range of topics, including data manipulation, control flow structures, and advanced Python features. With a hands-on approach and real-world programming scenarios, learners will develop the ability to create powerful applications and solutions using Python. This course bundle is ideal for anyone interested in programming or seeking to enhance their programming skills. Whether you're a student, a professional looking to switch careers, or an experienced programmer seeking to learn a new language, "Ultimate Python Programming Masterclass" is the perfect way to take your skills to the next level. Ultimate Python Programming Masterclass Course Curriculum Section 01: Introduction to Python Programming Section 02: Lists & Tuples Section 03: Strings Section 04: Dictionaries Section 05: Dictionaries Methods Section 06: Conditions, Loops and Statements Section 07: Abstraction-I Section 08: Abstraction-II Section 09: Exceptions Section 10: Magic Methods, Properties and Iterators Section 11: Standard Libraries Section 12: Reference Files How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 15 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Students interested in programming and computer science. Professionals seeking to enhance their programming skills. Entrepreneurs and business owners looking to create innovative solutions. Experienced programmers seeking to learn a new language. Individuals looking to switch careers and enter the field of programming. Career path Python Developer: £35,000 - £70,000 Data Analyst: £20,000 - £60,000 Machine Learning Engineer: £40,000 - £90,000 Software Engineer: £25,000 - £80,000 Web Developer: £20,000 - £55,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

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

Duration 1 Days 6 CPD hours This course is intended for This course is designed for data scientists with experience of Python who need to learn how to apply their data science and machine learning skills on Azure Databricks. Overview After completing this course, you will be able to: Provision an Azure Databricks workspace and cluster Use Azure Databricks to train a machine learning model Use MLflow to track experiments and manage machine learning models Integrate Azure Databricks with Azure Machine Learning Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this course, students will learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning. Introduction to Azure Databricks Getting Started with Azure Databricks Working with Data in Azure Databricks Training and Evaluating Machine Learning Models Preparing Data for Machine Learning Training a Machine Learning Model Managing Experiments and Models Using MLflow to Track Experiments Managing Models Managing Experiments and Models Using MLflow to Track Experiments Managing Models Integrating Azure Databricks and Azure Machine Learning Tracking Experiments with Azure Machine Learning Deploying Models

Duration 1 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Google Cloud Platform Big Data and Machine Learning Fundamentals 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.

Data Analysis: Data Analysis Training Have you ever wondered how companies get insights from massive volumes of data to stay competitive and make wise decisions? If so, then participate in our exclusive Data Analysis: Data Analysis Course. This Data Analysis Course describes the fundamentals of data, statistics, and an introduction to Data Analysis. How to get data and where to find it is explained in the Data Analysis Course. Moreover, this Data Analysis Course covers data cleansing, preprocessing, and exploratory data analysis (EDA). Additionally, the Data Analysis Course provides an introduction to Python and Excel for Data Analysis. This thorough Data Analysis Course includes lessons on data wrangling with Pandas (python) and data visualisation using Matplotlib and Seaborn (python). Enrol in our Data Analysis Course to study the fundamentals of statistical analysis and machine learning. Main Course: Data Analysis (Data Analytics) Training Free Courses included with Data Analysis: Data Analysis Training Course: Course 01: Minute Taking Course 02: GDPR Course 03: Cyber Security [ Note: Free PDF certificate as soon as completing the Data Analysis: Data Analysis Training Course] Data Analysis: Data Analysis Training Online This Data Analysis (Data Analytics) Training consists of 12 modules. Curriculum of Data Analysis (Data Analytics) Training Course Module 1: Introduction to Data Analytics Module 2: Basics of Data and Statistics Module 3: Data Collection and Sources Module 4: Data Cleaning and Preprocessing Module 5: Exploratory Data Analysis (EDA) Module 6: Introduction to Excel for Data Analytics Module 7: Introduction to Python for Data Analytics Module 8: Data Wrangling with Pandas (Python) Module 9: Data visualisation with Matplotlib and Seaborn (Python) Module 10: Introduction to Basic Statistical Analysis Module 11: Introduction to Machine Learning Module 12: Capstone Project - Exploratory Data Analysis Assessment Method of Data Analysis (Data Analytics) Training Course After completing Data Analysis: Data Analysis Training Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Apart from this, you do not need to sit for any other assessments. Certification of Data Analysis (Data Analytics) Training Course After completing the Data Analysis: Data Analysis Training Course, you can instantly download your certificate for FREE. The hard copy of the certification will also be delivered to your doorstep via post, which will cost £13.99. Who is this course for? Data Analysis: Data Analysis Training Online For business professionals, entrepreneurs, or anybody else looking to have a thorough grasp of data analysis in a commercial setting, this Data Analysis Course is ideal. Requirements Data Analysis: Data Analysis Training Online To enrol in this Data Analysis: Data Analysis Training Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Data Analysis Training Course. Be energetic and self-motivated to complete our Data Analysis Training Course. Basic computer Skill is required to complete our Data Analysis Training Course. If you want to enrol in our Data Analysis Training Course, you must be at least 15 years old. Career path Data Analysis: Data Analysis Training Online This Data Analysis Course will assist you in obtaining positions as a business analyst, marketing analyst, data analysis, and in related fields.

Step into the future of AI with our Prompt Engineering course! Master the art of prompt crafting for Dall-E, Stable Diffusion, ChatGPT, and more. Learn advanced techniques and best practices to optimize interactions with cutting-edge AI models.

Machine literacy in data wisdom is a fleetly expanding discipline and now is the crucial element. This groundbreaking field equips computers and systems with the capacity to learn from data and ameliorate their performance over time without unequivocal programming. Statistical ways are employed to train algorithms to produce groups or prognostications and to find significant findings in data mining systems. immaculately, the conclusions made from these perceptivity impact crucial growth pointers in operations and companies. What's Machine Learning? . Machine learning classes in pune The machine literacy term was chased by Arthur Samuel in 1959. It's the discipline solely concentrated on studying and erecting tools and ways that can let machines learn. These styles use data to enhance the computer performance of a particular set of tasks. Machine literacy algorithms induce prognostications or possibilities and produce a model grounded on data samples, also called training data. There's a need for machine literacy as these algorithms are applied in a broad range of operations, for illustration, computer vision, dispatch filtering, speech recognition, husbandry, and drugs, where it's a challenge to produce traditional algorithms that can negotiate the needed tasks. orders in Machine Learning Being such a vast and complicated field, machine literacy is divided into three different orders machine literacy orders Supervised literacy – In this system, the algorithm is trained using data that has been labeled and in which the target variable or asked result is known. Once trained, the algorithm may make prognostications grounded on unidentified information by learning how to associate input variables with the willed affair. Unsupervised literacy – In this case, the algorithm is trained on unlabeled data, and its thing is to discover structures or patterns within the data without having a specific target variable in mind. Common unsupervised literacy tasks include dimensionality reduction and clustering. underpinning literacy – An algorithm is trained via relations with the terrain in this type of literacy. The algorithm learns how to operate in order to maximize a price signal or negotiate a particular ideal. Through prices or penalties, it receives feedback that helps it upgrade its decision-making process. Artificial Intelligence and Machine Learning Artificial intelligence( AI) is divided into several subfields, and machine literacy( ML) is one of them. In order to produce intelligent machines that can pretend mortal intelligence, a variety of methodologies, approaches, and technologies are used. This notion is known as artificial intelligence( AI). The development of ways and models that allow computers to acquire knowledge from data and make recommendations or judgments without unequivocal programming is the focus of machine literacy( ML). Some academics were interested in the idea of having machines learn from data in the early stages of AI as an academic field. They tried to approach the issue using colorful emblematic ways and neural networks. They were primarily perceptrons, along with other models that were ultimately discovered to be reimaginings of the generalized direct models of statistics. For this case, you aim to make a system secerning cows and tykes. With the AI approach, you'll use ways to make a system that can understand the images with the help of specific features and rules you define. Machine literacy models will bear training using a particular dataset of pre-defined images. You need to give numerous farmlands of cows and tykes with corresponding markers. Why is Machine Learning Important? Machine literacy is an abecedarian subfield of artificial intelligence that focuses on assaying and interpreting patterns and structures in data. It enables logic, literacy, and decision-making outside of mortal commerce. The significance of machine literacy is expanding due to the extensively more expansive and more varied data sets, the availability and affordability of computational power, and the availability of high-speed internet. It facilitates the creation of new products and provides companies with a picture of trends in consumer geste and commercial functional patterns. Machine literacy is a high element of the business operations of numerous top enterprises, like Facebook, Google, and Uber. Prophetic Analytics Machine learning course in pune Machine literacy makes prophetic analytics possible by using data to read unborn results. It's salutary in the fields of finance, healthcare, marketing, and logistics. Associations may prognosticate customer growth, spot possible troubles, streamline operations, and take visionary action to ameliorate results using prophetic models. Personalization and recommendation systems Machine literacy makes recommendation systems and substantiated gests possible, impacting every aspect of our diurnal lives. Platforms like Netflix, Amazon, and Spotify use machine literacy algorithms to comprehend stoner preferences and offer substantiated recommendations. Personalization boosts stoner pleasure and engagement while promoting business expansion. Image and speech recognition Algorithms for machine literacy are particularly good at jobs like speech and picture recognition. Deep literacy, a branch of ML, has converted computer vision and natural language processing. It makes it possible for machines to comprehend, dissect, and produce visual and audio input. This technology is helpful for driverless vehicles, surveillance, medical imaging, and availability tools, among other effects. Machine learning training in pune

Overview With the ever-increasing demand for Data Analysis Level 3 Diploma in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Data Analysis Level 3 Diploma may be. Learning about Data Analysis Level 3 Diploma or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Data Analysis Level 3 Diploma . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Data Analysis Level 3 Diploma is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Data Analysis Level 3 Diploma course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Data Analysis Level 3 Diploma course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Data Analysis Level 3 Diploma course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Data Analysis Level 3 Diploma , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Data Analysis Level 3 Diploma , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Data Analysis Level 3 Diploma , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Data Analysis Level 3 Diploma course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams.     Course Curriculum Module 1 Introduction to Data Analysis. Introduction to Data Analysis. 00:00 Module 2 Mathematics and Statistics. Mathematics and Statistics. 00:00 Module 3 Data Manipulation. Data Manipulation. 00:00 Module 4 Data Visualisation. Data Visualisation. 00:00 Module 5 Data Wrangling. Data Wrangling. 00:00 Module 6 Data Exploration. Data Exploration. 00:00 Module 7 Machine Learning Fundamentals. Machine Learning Fundamentals. 00:00 Module 8 Machine Learning Algorithms. Machine Learning Algorithms. 00:00 Module 9 Data Analysis with Python and Libraries. Data Analysis with Python and Libraries. 00:00 Module 10 Data Analysis with R and Libraries. Data Analysis with R and Libraries. 00:00