AI Artificial Intelligence for Digital Marketing Workshop

Learn How (AI) Artificial Intelligence can do for your Digital Marketing

The predictable AI capabilities bring a new era of commercialization. According to a recent whole world digital marketing audience report, 86% of marketers believe AI will perform more efficient and effective work in today’s complex digital environment.

AI – Artificial Intelligence Will Predictive Digital Marketing Soon

In fact, AI predictive marketing can change the whole world marketing’s game. This allows companies to anticipate the needs and concerns of consumers and, more importantly, predict marketing information. For organizations that seek to strengthen customer participation, the information is clear. This is because the people who are primary predictors of innovation are likely to succeed. Digital Marketing platform across Google, Facebook, Twitter, Instagram, WhatsApp, SEO, SEM, Youtube and etc.

AI Artificial Intelligence for Digital Marketing Workshop

AI Artificial Intelligence for Digital Marketing Workshop

 

Big Data Analytics in Business and Your Digital Marketing Big Data

The main cause of this popularity and growth of “Big Data” in today’s world is not other than the growth of the smartphones, social media, internet technology, wireless networks and other technologies.

Over the past few years the trends that have revolutionized the internet world, big data is also one of those. The term “Big data” may have been around since past few years but still, for many of us, it is somewhat confusing. Basically, big data is a broad topic, used to define large data sets that can be computationally analyzed to reveal trends, patterns and associations – principally in connection with human interactions and behavior. The main cause of this popularity and growth of “Big Data” in today’s world is not other than the growth of the smartphones, social media, internet technology, wireless networks and other technologies.

 

How Is Big data Important?
The practical implementation of “Big data” can be observed across a wide range of areas, including businesses. Big data is followed by the simple working principle which states that the more you will be having data about anything or situation, the more you will be able to predict it’s future. Now if talk about the importance of Big Data, it doesn’t depend on the volume of data you have but it must revolve around, what you will do with that data and what is your approach to analyze that data?. By analyzing “Big Data”, one can be able to provide his/her solution for cost reduction, making strategic decisions, developing a new product and time reductions as well. It is said that “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” – Geoffrey Moore
A combination of Big data along with its analytics can help you to achieve different tasks. To sketch a clearer picture of big data and the way it can be advantageous to you, the following convoluted analysis can be used for:

AI ARTIFICIAL INTELLIGENCE FOR DIGITAL MARKETING WORKSHOP

AI ARTIFICIAL INTELLIGENCE FOR DIGITAL MARKETING WORKSHOP

 

Machine Learning in Business & Marketing

Since years ago, 2010, queries related to venture capital, conference, marketing, and business-related “machine learning” are increasing substantially, most technical executives often can decide the machine application learning (ML) for business application.

Behind few of the greatest advancements in technology like autonomous vehicles, there is an emerging force of science, which is known by the name Machine learning. Machine learning is the field of science that is a reason behind the development of new world concepts, in both supervised and unsupervised way of learning. On the other hand, it has also enabled the human to build such algorithms, which are useful in building close to the real robots, analytics tools, chatbots and internet of things devices etc.

If we define Machine learning in few words, it can be termed as the subset of “AI” that provides the automatic learning ability to a system with constant improvements through experiences. The best thing about machine learning is that you don’t have to program every single action because the computer applies pre-configured data sets and rules to perform even complex calculations.

 

The Future Of Today’s World of Machine Learning in Business
If you look around, you will find most of today’s businesses are relying on machine learning algorithms these days in order to have a better understanding of their customers and returns opportunities. It has played a great role in transforming the digital world and has made our computing process simpler, reliable, and cost-effective. For the companies that have started practicing machine learning algorithms, machine learning is playing a great role in helping them to provide better customer care experiences, optimized operations and enhancing their security etc. In short, machine learning has changed the ways world used to business in many ways. In this article, we are going to highlight a few impacts of machine learning that can be observed in today’s business world.

 

Personalized search experience
With the advancement in machine learning algorithm, websites and applications these days are learning customer’s preferences for stuff like food, clothing, electronics and other products. Businesses are adopting machine-learning algorithms to enhance the overall online shopping experience by suggesting customers the products that fit their preferences just by collecting and analyzing the different sets of data.

 

Customer Services
Machine learning has greatly transformed the customer support services, and efficient chatbots algorithms nowadays answer more than 80% of customer queries, which really cut operator expenses.

 

Rectified Search results
Search engine these days are getting better than those of the past times do. Nowadays search engines understand what it’s user is trying a search and provide the most relevant information acquired by the user. Long things short, Machine-learning tactics are being arrayed to solve a different kind of problems based on different kind of scenarios and with current advancements in machine learning these days, it is hard to imagine a scenario where a machine learning couldn’t be of any use. According to the business applications, machine-learning methods can be deployed to perform few more things like things like:
• Build accurate pricing models
• Identify network interferences
• Generating real-time advertisement on websites for targeted audiences
• Improvement of demand forecasts in retails businesses
• Can be used to identify any fraud in real time (Gmail spam box is a practical example of this)
• And many others

 

Verdict
Machine learning is playing a major role in helping businesses create better experiences while enhancing the security and efficiency of the processes. Anyhow, machine learning requires the learning of high-quality data to reach its full perspective. Therefore if you want to use machine learning to understand data and make a fruitful prediction for the growth of your business join today machine learning in business course that could be of great use for the better future of your business.

 

Targeting And Understanding The Right Audience
This one can be claimed as the most broadcasted and biggest areas where utilizing big data is practiced today. In this area, big data is used to have the better understanding of customers, their preferences and behaviors. Now when your business starts knowing about customer’s preferences, you will have an advantage over your competitor then.
An Upbeat Customer Service
With the use of Big data now, businesses would be able to specify their customer needs, even before their customer feel the need to voice his/her concerns.
Consumer responsive production
The use of big data will not only enhance the customer services but it will also help the company to manufacture customer responsive products. Therefore, better than asking your customers about what they need to see in your product, you can simply go for big data analysis to predict what they are looking for in a product.

 

Risk management
Investments are always risky because of you never sure about the returns. Anyhow, by utilizing big data analysis a business can have a more comprehensive picture of success or failure rate. Though whenever there is an investment, there must a risk but by using big data, the percentage of failure risk can be minimized.

AI ARTIFICIAL INTELLIGENCE FOR DIGITAL MARKETING WORKSHOP

AI ARTIFICIAL INTELLIGENCE FOR DIGITAL MARKETING WORKSHOP

 

Improved Efficiency
To increases, the performance of the particular process, looking into its data is very important. Now with big data analysis, experts can easily find binding constraints in that particular process. Once those constraints are found and removed a huge increase in performance can be observed.

Last but not the least big data is something that you will have to embrace if you need your business keep on growing. With the power of big data analysis, you can predict the future of your businesses but to have a focused picture of big data, a brief knowledge of Big data and its analysis procedures is required. In order to thrive and succeed in today’s business world big data marketing courses are offered through various platforms and enrolling in those courses can be quite productive for you and your businesses.

Workshop Photos Gallery

AI for Digital Marketing

AI artificial Intelligence for digital marketing workshop

Artificial Intelligence Training Course in Digital Marketing

Artificial Intelligence Training Course in Digital Marketing

Building Artificial Intelligence Services

Building Artificial Intelligence Services

Reach – Use various inbound technologies to reach visitors

Coverage involves using technologies such as content marketing, search engine optimization, and other “earned media” to bring visitors to your website and start their buyer journey. Artificial intelligence models and trendy apps can be used at this stage to attract more visitors and provide a more engaging experience for your website.

artificial intelligence facebook marketing course malaysia

artificial intelligence facebook marketing course malaysia.jpg

1. AI generates content

This is a very attractive AI area. Artificial Intelligence can not write a political opinion or blog article on industry-specific best practices advice, but content generated by artificial intelligence in some areas can be useful and help attract visitors to your site.

For some features, AI content compilers can select elements from the dataset and build a “human exploration” article. AI author named “WordSmith” produces 1.5 billion copies in 2016 and is expected to continue to be popular in the coming years.

The author of AI is very useful for reporting organized events and data. Examples include quarterly earnings reports, sports events and market data. If you operate in areas such as financial services, the resulting AI content may be part of your content marketing strategy. The good news is that the automation vision that the companies behind Wordsmith have announced is a free beta version of its AI writing application so you can try out the technology and see if it might be useful for your brand.

artificial intelligence course malaysia

artificial intelligence course malaysia

2. Smart content management

The content policies supported by AI enable you to further attract your visitors by showing relevant content. This technique is most commonly found in the “Buy X Buyers Also Purchase Y on Many Pages” sections, but they can also be used for blogging and messaging content that is more widely available on the web. This is also a good technique for subscribing to business, and more and more people are using this service, the more data to use machine learning algorithms and better content suggestions. Think of the Netflix backup system to continue to recommend you, indicating that you are interested.

Deep Learning Algorithms Course Malaysia

Deep Learning Algorithms Course Malaysia

3. Voice search

Voice search is another artificial intelligence technology, but when marketing, it uses technology developed by major players (Google, Amazon, Apple) rather than developing its own capabilities. Voice search will change the future of SEO strategies, brands need to compete. As virtual artifacts driven by artificial intelligence adds to voice search traffic, brands that determine voice search can take advantage of high buying intentions to capitalize on the huge profits of organic traffic.

4. Purchase programmed media

Programmatic media buys can use trend models generated by machine learning algorithms to target ads more effectively to the most relevant customers. After Google’s latest brand security scandal, programmatic advertising needs to be smarter. It has revealed that programmatic advertisements through the Google advertising network appear on terrorist websites. Artificial Intelligence can help identify the site and remove it from the list of sites that can be placed.

Action – Attract visitors to tell them about your product

5 tend to model

As previously mentioned, modeling tendencies is the goal of machine learning programs. Machine learning algorithms provide a lot of historical data and use this data to create a trend model that, in theory, can make accurate predictions about the real world. The easy chart below shows the stage of this process.

 

6. Prediction analysis

Propensitive modeling can be used in many different fields, such as predicting the possibility of a specific customer conversion, predicting prices that can be changed by customers, or customers who are likely to repeat the purchase. This app is called forecasting analysis because it uses analytics data to predict customer behavior. The important thing to keep in mind is that the model, as good as a model of inclinational tendency to provide data, so if there is a high-level error or random data, you can not make accurate predictions.

7. The main score

The trend model created by machine learning can be trained to score potential customers based on a set of criteria so that your sales team can determine how “hot” a given leader is worth production. In the B2B business with the sales process of negotiations, it is very important for the sales team to spend a lot.

8. Advertising targeting

Machine learning algorithms can run large amounts of historical data to determine which ones are best for people and at any level during the purchase process. Using this data, they can give them the most effective content at the right time. By using machine learning to continuously optimize thousands of variables, you can achieve more effective ad placements and ad content than traditional methods. However, you still need humans to do creative parts!

Transform – Raise interests of interested users to customers

9. Dynamic price

All marketers know that effective sales lead to more products. Discounts are very powerful, but they can also hurt your bottom line. If you double your sales with two thirds of your small profits, then you will have less profits than you would have been without sales.

Sales are very effective because they allow people to buy your product and never think they can justify the purchase cost. But they also mean that people who pay higher prices pay less than they pay.

Dynamic pricing avoids this problem by targeting specific bids only to users who need to convert. Machine learning can create a trend model whose characteristics indicate that the customer may need to convert quotes and may change without quoting. This means you can maximize sales by increasing sales without sacrificing profitability.

10. Custom Web & App

Using a trend model to predict the customer phase in a buyer’s journey allows you to provide the customer with the most relevant content on an application or web page. If someone on your site is a novice, the content that informs them and makes them interesting will be the most effective, and if they visit it many times and are interested in the product, the more in-depth content about the benefits of the product will be better .

11. Chatbots

Chatbots mimic human intelligence by explaining the user’s problems and completing their orders. You might think chat robots are hard to develop and only big budget big brands can develop them. But in fact, using the open chatbot development platform, it’s fairly easy to make your own chat robot without a lot of developers.

Facebook is interested in promoting the development of branded chatbots. He wants his Messenger application to be where people talk to brand ambassadors. The good news with this brand is that this means they can use some of Facebook’s powerful bot development tools. Using the lessons they learned from the “M” beta (Facebook Messenger’s own chat robot), Facebook created a smart boat engine that lets you train ships through example dialogues and keep your ship engaged with your customers. If you are interested in creating a chat robot for your brand on the messenger platform, Facebook has created useful tutorials that you can find on their Facebook page.

12. Aim again

Like ad targeting, machine learning can be used to determine from historical data which content is most likely to return a customer to a website. My building is an accurate predictive model and what kind of content is most effective for winning different types of clients, machine learning can be used to optimize your targeted ad to make it work.

Engage – get your customers back

13. Predict customer service

It’s easier to attract new customers by duplicating existing customer groups. So keeping the existing happy customer is the key. This is especially true in subscription-based services, where high churn prices can be very expensive. Predictive analysis can be used to determine which customers are most likely to cancel a subscription service, customers unsubscribe by evaluating who has the most common. It is then possible to reach these customers by offering, encouraging or helping to prevent them from beating.

14. Marketing Automation

Marketing automation technology often involves some rules when these rules force active engagement with customers. But who decides this rule? In general, marketers basically guess what works best. Machine learning runs through billions of customer data points and determines when it is the most effective contact time, and what words in the subject line are most effective. This vision can be used to improve the effectiveness of marketing automation efforts.

15 1: 1 dynamic email

In the same way as marketing automation, applying the insights generated by machine learning can create a highly effective 1: 1 dynamic email. Predictive analysis using a trend model may be inclined to set up several categories, sizes and colors from users buying through your previous actions, and showing the most relevant products in communication. When opening email, product inventory, trading, price is correct.

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Data Science for Real-Business Big Data Analyze Course

Data Science for Real-Business – Big Data Analyze Training Course Malaysia

Big data age is a long time, but there is no doubt that its influence has been felt. Can the future of marketing work be attributed to data science?

Data Science for Real-Business - Big Data Analyze Training Course Malaysia

Data Science for Real-Business – Big Data Analyze Training Course Malaysia

The digital marketing technology industry continues to attract me even if software vendors are saturated. Recently, I spend more time on data science, refer to recent posts in my social media platform. However, before discussing how marketing benefits from data science, I think it’s important to discuss the scope of marketing techniques.
If you follow the growth of marketing technology, it’s easy to lose in the new data ocean technology.

Marketing Data Director (Medium Salary: estimated 200K annual): We all know that marketing data grows fast and requires a huge database. For most organizations that rely on business intelligence (BI) or IT, marketing data management is a big challenge. BI and IT have their own priorities and rely on how your organization organizes marketing data management can not be their top priority.

Interestingly, this role is also a mixture of analytical / BI and marketing skills sets. An ideal candidate may be an experienced business intelligence person who spent most of his time helping the marketing team to understand the practice of modern marketing. Marketing analysts with strong data skills can also play a role.

  • Successfully perform all steps in a complex Business Data Science project
  • Perform Data Mining in Business
  • Understand how to apply the Chi-Squared statistical test
  • Apply Ordinary Least Squares method to Create Linear Regressions
  • Assess R-Squared for all types of models
  • Assess the Adjusted R-Squared for all types of models
  • Create Dummy Variables
  • Interpret coefficients of an MLR
  • Read statistical software output for created models
  • Use Backward Elimination, Forward Selection, and Bidirectional Elimination methods to create statistical models
  • Create a Logistic Regression
  • Intuitively understand a Logistic Regression
  • Operate with False Positives and False Negatives and know the difference
  • Read a Confusion Matrix
  • Create a Robust Geodemographic Segmentation Model
  • Transform independent variables for modelling purposes
  • Derive new independent variables for modelling purposes
  • Check for multicollinearity using VIF and the correlation matrix
  • Understand the intuition of multicollinearity
  • Apply the Cumulative Accuracy Profile (CAP) to assess models
  • Build the CAP curve in Excel
  • Derive business insights from the coefficients of a logistic regression
  • Understand what model deterioration actually looks like
  • Apply three levels of model maintenance to prevent model deterioration
  • Install and navigate SQL Server
  • Install and navigate Microsoft Visual Studio Shell
  • Clean data and look for anomalies
  • Use SQL Server Integration Services (SSIS) to upload data into a database
  • Deal with Text Qualifier errors in RAW data
  • Create Scripts in SQL
  • Apply SQL to Data Science projects
  • Create stored procedures in SQL
  • Present Business Data Science projects to ready use
Who is the target audience?
  • Someone wants to master stats for business analytics
  • Someone who wants to learn stats from the ground up
  • Someone who wants to get hands-on experience with Business Data Science

Comprehensive introduction to your business data analysis teaches you how to apply different data analysis methods to make your data a new insight and intelligence. The ability to ask is a strong competitive advantage that leads to new sources of income, better results and productivity gains. The report recently stated that data analysis is one of the most important skills in Malaysia economy today. This course focuses on the following different analysis methods. In this lesson, you will learn why the form of analysis is important and provide examples using Excel 2013 for analysis.

Artificial Intelligence Course Malaysia

Artificial Intelligence – How To Build An Complete Artificial Intelligence – Training Course Workshop

This course all about Mix the power of Big Data, Machine Learning and Deep Learning to create most and only powerful AI – Artificial Intelligence for Daily Life Real-World applications to apply to every single holes in this world. 

artificial intelligence course malaysia

artificial intelligence course malaysia

Artificial Intelligence and Business Strategic Plans are exploring the increased use of artificial intelligence in a business environment. This exploration illustrates how AI – Artificial Intelligence influences the development and implementation of an organization’s strategy. Artificial intelligence (AI) is interrupted here, but many business leaders do not know the expectations of AI and how they fit into their business model. But with the rapid development of change, it is time to determine your company’s AI – Artificial Intelligence strategy

What will you learn in this AI – Artificial Intelligence Course Malaysia?

  • Make AI – Artificial Intelligence for real daily usage
  • Understand the theory behind artificial intelligence
  • Create a virtual self-drive
  • Make AI -Artificial Intelligence to beat the game
  • Use AI -Artificial Intelligence to solve real world problems
  • AI -Artificial Intelligence master art model
  • Artificial Intelligence – Deep learning
  • Understand whether the distribution is normal
  • Understand the standard deviation
  • Explain the differences between continuous and discrete variables
  • Understand side-by-side distribution
  • Understand the central limit theorem
  • In practice, central limit theorem is used
  • Application of hypothesis test is meaningful
  • Use the hypothesis to test the ratio
  • Use Z-Score and Z-Tables
  • Use t-mark and t-table
  • Understand and apply statistical interests
  • Make a confidence interval
  • Understand the potential for too many p-values

This Artificial Intelligence course is about intersection of Artificial Intelligence linked with business strategy: Understand the artificial intelligence environment and predict the impact of artificial intelligence on customer products, processes, organizational capabilities and competitive advantage / weakness.

Learn about AI concepts and critical intuitive exercises to speed up all AI’s speed, it include:

  • How to start AI build without having to use Python’s coding
  • How to combine AI with OpenAI Gym
  • How to optimize your AI to achieve its maximum potential in the daily real world

1. Complete beginner AI expert skills – learn to set up a series of uses for your own AI enhancement. Each tutorial starts with a blank page, and we write the code from scratch. In this way, you can follow the summary of the code and the meaning of each line.

2. AI Artificial Intelligence Templates – In addition, you will get a downloadable Python code template for each AI you build in. This makes AI very unique because it is easy to change multiple lines of code. If you let go of your imagination, the potential is endless.

3. Intuitive Networks – We do not throw complex maths on you, but focus on building your own intuition to encode AI, making infinite better results possible.

4. Real-world solutions – you will not only achieve goals in one game, but also in three games. Each module consists of different structures and difficulties, which means that you will be able to master the AI ​​that adapts to the environment in real life, rather than testing “tests and forgetting” like most other courses.  Do AI Practice is absolutely make you perfect.

 

Who is our Artificial Intelligence Course target audience?
  • Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning.

 

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DEEP LEARNING COURSE MALAYSIA

Artificial Intelligence Complete Course: Deep Learning Course Malaysia

This makes a great of machine learning adds extra elements – this opportunity to damage the pedals after our own proverbs. We can use machine learning techniques, not for TV races and board games, but for our own complex and related to your business. In other words, it can make you money.

How Can Deep Learning Help My Business?

It’s easy to understand that companies like Google, Facebook, Amazon, Apple, and other learning machines are powerful tools for they. They are in the big data business. But from the above can be seen, beer, personal loans, oil wells, basketball – most companies are the same, or soon in the future. “Big data” has been used for several years. Most companies are on the train. The CEO and CTO acknowledge that there is value in collecting all the data in the business process for future market! Deep learning will help companies develop less retrograde and predictive models in terms of revenue, and what to do or build or prepare in your business is more thorough. Companies like Google, Facebook, Amazon, Apple have already begun offering a lot of software tools to get started. They will also provide engineering help (price) to get you started. Without question, driving millions of kilometers away, IBM Watson diagnosed patients better than doctors, Google Deepmind AlphaGo has beaten Go world champion last few month.

But the progress of AI – Artificial Intelligence – Deep Learning further, the more complex the problem. Only deep learning can solve complex problems, which is the cause of artificial intelligence. 

Deep Learning Algorithms Course Malaysia

Deep Learning Algorithms Course Malaysia

Who Should Join This Artificial Intelligence – Deep Learning Workshop

You can see that there are many different tools in the field of learning. In this course we will show you the most important and up-to-date tools so that when you have finished studying from 0 till 100, your skills are sophisticated today’s technology.

A real world deep learning case study

Mastering in immersive learning is not just about intuitions and tools, but also apply these models to real-world scenarios and achieve measurable results for businesses or projects. That’s why we introduced exciting challenges in this deep learning course for you, will bring you into Artificial Intelligence network.

In this deep learning chapters:

1 Deep Learning Churn Model

Your goal is to create an artificial neural network that can be used to predict any individual customer who leaves the bank or resides (customer churn) based on the geographical demographic information and transaction information described above. In addition, you are required to rate all customers based on the probability of their departure. To do this, you need to use the correct depth learning model, model based on probabilistic method.

2 Deep Learning into Image Recognition

Creates a convolutional nerve network or we called CNN detects multiple objects in the image. We will implement this depth learning model to identify a group of lions or tigers in a set of images. However, this model can be reused for any other content, and we will tell you how to do it by simply changing the image in the input datasets folder.

3 Deep Learning -Stock Price Prediction Model

You will create a depth learning model in deep learning – that is closest to Artificial Intelligence. This is because the model will be long memories, just like us, humans. A significant improvement in the frequent neural network has led to the popularity of (long time memory RNN), which completely changed the AI Artificial Intelligence playground. We are very excited to incorporate these cutting-edge in-depth learning methods into our deep learning courses! We will take the challenge to use it to predict the real Google stock market price.

4 Deep Learning – Fraud Detection Model

Market and market forecast fraud predicted market forecasts will reach $ 331.9 billion in 2021. This is a huge industry, the demand for complex depth of learning skills will only grow. That’s why we included the reason for this case study in this deep learning course. Unsupervised Deep Learning Models, here is the data provided by the customer when completing the application form. Your job is to detect possible fraud in this application. This means that before the end of the challenge, you’ll be providing a clear list of customers who are cheat their own application of credit card.

5 Deep Learning – Recommender Systems Model

Suggestions – A good recommendation system is very valuable in today’s business world. And the experts who created it were some of the achievements that several scientists had done in Artificial Intelligence Network World. We will deal with a set of data that has the same functionality as the Facebook data set: a large number of images, and thousands of users evaluating the images / video they are watching. Rating from like, wow, love, angry, as in Facebook datasets, this makes building systems more complicated than if the ratings just “like” or “dislike”. In this recommender model will be the political network of the composite machines. Then our model will be my powerful AutoEncoders, my personal favorite. You will appreciate their simplicity and the difference they can afford.

What you going to get from this course?

  • What is the intuition behind Deep Learning – Artificial Neural Networks
  • Apply Artificial Neural Networks in your real world situation
  • Find out the intuition behind Convolutional Neural Networks – CNN
  • Apply your Convolutional Neural Networks in business world
  • Apply Recurrent Neural Networks in practice
  • Understand the intuition behind Self GPS – Organizing Maps
  • Apply Self-Organizing Maps in human daily life
  • Understand the intuition behind AutoEncoders
  • Apply AutoEncoders in practice

 

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Machine Learning Course Malaysia

Artificial Intelligence Complete Course: Machine Learning Course Malaysia

Machine learning is a subset of artificial intelligence, which uses computer algorithms from the main learning data and input information. In the machine learning models, we doesn’t need detailed programming, but we can change and improve their own algorithms to ensure it can self learning and improve!

machine learning course malaysia singapore thailand bangkok kuala lumpur

machine-learning-course-malaysia

Career opportunities for data science, large data and analysis are growing rapidly. This is one of the most sought after jobs in the technology sector today. If you are interested in changing your career path, determine the right way to study, or decide whether the certification is worth your time, this course will serve you – Artificial Intelligence – Machine Learning Course.

  • Understanding Machine Learning using Python 
  • Study deep intuition of Machine Learning models
  • Make accurate business predictions related to your field
  • Make complete powerful big data analysis
  • Create robust Machine Learning models with simple steps
  • Create strong added value to your business
  • Apply Machine Learning for daily purpose
  • Understand contents like Reinforcement Learning, Deep Learning & Artificial Intelligence Learning
  • Apply which Machine Learning model to choose for your problem in business purpose
  • Build an complete web of powerful Machine Learning models and know how to combine them to solve any problem

Started to Learn Machines Learning with simple steps today

Interested in creating Machine Learning models? Then this machine learning course is for you!

This  machine learning course contents has been written by two professional Data Scientists so that we can share our knowledge and help you learn Artificial Intelligence – Machines Learning theory, business algorithms and coding libraries in a just few simple way.

We will gradually to learn introduce machines to your world. With every tutorial you will develop new skills and improve your understanding of this challenging of these sub-field of Machine Learning -Data Science.

Learning machine-learning based learning or self improvement algorithms … In machine learning, computers start from the model and constantly tested by itself with trials and errors … and then it gives a meaningful vision in the form of classification, Forecast and grouping … There are two machine learning type: one ( supervised ) and the other ( unsupervised ) can not be controlled. Hereby, this process is a cumulative classification, … mining areas and data analysis used in the concept … in the unsustainable learning environment and we called it as Artificial neural networks (ANNs).

How real businesses are using machine learning

Big companies are investing in Artificial Intelligence – Machine learning Models… because they’ve seen positive Future for Marketing, management and problem solving.

Everyone wants to minimize losses and maximize profits for their business and related field. Artificial Intelligence – Machine learning Models and Learning Deep change the way we understand the software, making the computer more intelligent than ten years ago. As a result ofArtificial Intelligence – Machine learning Models and improvement methods for data analysis, data analysts and data scientists are increasingly using data to make informed decisions.

However, the Machine Learning course is come with practical exercises which are based on realistics live examples. So not only you going to learn the theory, but you will also get all the hands-on practice building your own useful models for your business machine learning models or personal machine learning models. As full bonus, this machine learning course includes Python complete code templates which you can download and use on your multiple projects. This Machine learning course is a must and exciting, at the same time we will fall deep into Machine Learning.

What is the target audience?

  • Web developers
  • Entrepreneurs
  • Hard-working individuals
  • People who want to build a business
  • Anyone interested in Machine Learning
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning
  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
  • Anyone who are not with coding but who are interested in Machine Learning and want to apply it easily on datasets.
  • Any students in college who want to start a career in Data Science.
  • Any data analysts who want to level up in Machine Learning.
  • Someone line to become a Data Scientist.
  • Businessman who want to create added value to their business by using powerful Machine Learning tools

This is structured the Machine Learning following way:

Machine Learning Course Content:

  1. Applications of Machine Learning
  2. Why Machine Learning is the Future
  3. Recommended Anaconda Version
  4. Installing Python and Anaconda (MAC & Windows)
  5. Get the dataset
  6. Importing the Libraries for references
  7. Importing the Dataset / Big Data
  8. Python learners- summary classes & objects
  9. Missing Data
  10. Grouping Categorical Data
  11. Splitting the Dataset/Big Data into the Training sample
  12. Working Directory
  13. Data Preprocessing
  14. Logistic Regression
  15. Decision Tree Classification
  16. Random Classification
  17. Evaluating Classification Models Performance
  18. Artificial Neural Networks
  19. Convolutional Neural Networks

Download the Machine Learning course malaysia for Machine Learning Course Details from Us


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