PG Program in Artificial Intelligence Deep Learning Institute With Most Advanced Course Curriculum
Why is artificial intelligence important?
This technology influences consumer products and has led to significant breakthroughs in healthcare and physics and altered industries as diverse as manufacturing, finance, and retail.
Our legal institutions, media companies, financial institutions, and insurance companies are all figuring out ways to use artificial intelligence (AI) to their advantage. From fraud detection to writing news stories with natural language processing (NLP) and reviewing law briefs, AI's reach is widespread.
As business leaders and innovators race to reach artificial intelligence's promise to deliver a competitive advantage and cost-effectiveness and time savings, the technology shifts industries from finance to manufacturing with new products, processes, and capabilities.
Artificial intelligence can help improve our healthcare system. From personalized drug protocols to excellent diagnostic tools and even robots to assist in surgeries, AI is changing our healthcare system from its processes to the care these organizations provide.
Demand for AI professionals?
The World Economic Forum estimates that AI may lead to an increase in job openings globally.
Every other industry is trying to implement AI to cut costs and make it easier to operate business functions.
The research report by Component, Technology (ML, Computer Vision, NLP), Industry (Electronics, Energy, Automotive, Metals & Machine, Food & Beverages) Application (Cybersecurity, Robot, Planning), - Global Forecast to 2027 provides an in-depth analysis of AI in manufacturing market in five significant geographies. It emphasizes the current market trends, market size, market share, recent developments, and forecast until 2027. Artificial Intelligence (AI) in the manufacturing market is expected to reach $27 billion by 2027, growing at a CAGR of 39.7% from 2019 to 2027.
The North American region is estimated to command the largest global AI share in the manufacturing market in 2020.
Become an artificial intelligence professional today
There is an increasing necessitate for intelligent and correct decision-making across industries. This has led to an exponential growth in the adoption of AI and ML technologies, and they are expected to remain significant in years to come.
That's why Madrid Software Institute has got you a PG program in artificial intelligence in Delhi with 100% job assistance and classroom or online training by industry professionals who hold excellent knowledge with years of experience in the field.
Completing the program from the best AI training insitiute in Delhi will make you eligible for the international certificate by Hewlett Packard, helping you stand out from your competitors and acquire a highly paid position in top leading MNCs.
Enroll Now & Get Hired By Top MNC’s By Upgrading Your Skill On Various Technologies
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- Upgrade Your Skills For a High Paying Corporate Job
- Learn From Industry Leaders
- Develop Real World Projects
- Work on Multiple Case Studies
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Academic Partner - Hewlett Packard
What Is PG Program in Artificial Intelligence Deep Learning Course & Why It Is The Most Demanding Skill Now a Days?
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Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart human-like machines capable of performing tasks that usually require human intelligence. Artificial intelligence is an interdisciplinary science with multiple approaches, but advancements in machine learning(ML) and deep learning(DL) create a paradigm shift in virtually every tech industry sector.
Artificial intelligence (AI), a digital computer, or a computer-controlled robot can perform tasks commonly associated with intelligent beings.
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PG Program in Artificial Intelligence Deep Learning Course Highlights !
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Course Outline
Our PG Program in Artificial Intelligence Deep Learning Is Designed By Industry Experts That Gives The Candidate an Edge In The Market
- Introduction To Data Science
- Python Concepts
- Analytics Concepts Of Python
- Numpy Package
- Introduction To Pandas
- Data Manipulation Using Pandas
- Pandas Package
- Data Munging With Pandas
- Data Visualization With Matplotlib
- Data Cleaning Techniques
- Predictive Modeling Concepts
- Machine Learning Concepts
- Statistics
- Unsupervised Learning
- Supervised Learning
- principal component analysis
- Random Forest
- Support Vector Machine
- Case Studies
- Capstone Projects
Job Profile And Salaries Of PG Program in AI
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PG Program in AI Deep Learning Interview Q & A
1.What is logistic regression in Data science?
Logistic regression measures the relationship between the dependent variable (our label of what we want to predict) and one or more independent variables (our features) by estimating probability using its underlying logistic function (sigmoid). Logistic Regression is also called as the logit model. It is a method to forecast the binary outcome from a linear combination of predictor variables.
2.Differentiate between univariate, bivariate, and multivariate analysis ?
- Univariate - Univariate data contains only one variable. The purpose of the univariate analysis is to describe the data and find patterns that exist within it.
- Bivariate - Bivariate data involves two different variables. The analysis of this type of data deals with causes and relationships and the analysis is done to determine the relationship between the two variables.
- Multi-variate - Multivariate data involves three or more variables, it is categorized under multivariate. It is similar to a bivariate but contains more than one dependent variable.
3.How does data cleaning play a vital role in the analysis?
Dirty data often leads to the incorrect inside, which can damage the prospect of any organization. For example, if you want to run a targeted marketing campaign. However, our data incorrectly tell you that a specific product will be in-demand with your target audience; the campaign will fail.
4.What is the difference between supervised and unsupervised machine learning?
Supervised machine learning – It used unknown and labeled data. It has a feedback mechanism. The most commonly used supervised ML algorithms are decision trees, logistic regression, and support vector machines.
Unsupervised machine learning – It doesn’t require labeled data. Unlike supervised machine learning, it has no feedback mechanism. k-means clustering, hierarchical clustering, and apriori algorithm are the most commonly used unsupervised algorithms.
5.Explain the Decision Tree algorithm in detail?
A decision tree is a popular supervised machine learning algorithm. It is mainly used for Regression and Classification. It allows breaks down a dataset into smaller subsets. The decision tree can able to handle both categorical and numerical data.
6.What do you understand by the term recommender systems? Where are they used?
A subclass of information filtering systems that are meant to predict the preferences or ratings that a user would give to a product are recommender systems. Recommender systems are widely used in movies, news, research articles, products, social tags, music, etc. It helps you to predict the preferences or ratings which users likely to give to a product.
7.What is the p-value? What is its importance?
When you conduct a hypothesis test in statistics, a p-value allows you to determine the strength of your results. It is a numerical number between 0 and 1. Based on the value it will help you to denote the strength of the specific result.
p-value typically ≤ 0.05 shows strong evidence against the null hypothesis; so you reject the null hypothesis.
p-value typically > 0.05 shows weak evidence against the null hypothesis, so you accept the null hypothesis.
p-value at cutoff 0.05, this is considered to be marginal, meaning it could go either way.
8.We want to predict the probability of death from heart disease based on three risk factors: age, gender, and blood cholesterol level. What is the most appropriate algorithm for this case?
Choose the correct option:
- Logistic Regression
- Linear Regression
- K-means clustering
- Apriori algorithm
The most appropriate algorithm for this case is A, logistic regression.
9.Below are the eight actual values of the target variable in a train file. Find out the entropy of the target variable.
[0, 0, 0, 1, 1, 1, 1, 1]
Choose the correct answer.
- -(5/8 log(5/8) + 3/8 log(3/8))
- 5/8 log(5/8) + 3/8 log(3/8)
- 3/8 log(5/8) + 5/8 log(3/8)
- 5/8 log(3/8) – 3/8 log(5/8)
The target variable, in this case, is 1.
The formula for calculating the entropy is:
Putting p=5 and n=8, we get
Entropy = A = -(5/8 log(5/8) + 3/8 log(3/8))
10.Why do you want to be a data scientist?
The answer may vary from person to person. The aim is, to be honest, and polite. You may answer this like this. “I have a passion for working for data-driven, innovative companies. Your firm uses advanced technology to address everyday problems for consumers and businesses alike, which I admire. I also enjoy solving issues using an analytical approach and am passionate about incorporating technology into my work.”
FAQ
1. Who Should Do a Data Science Course?
Beginners and working professionals, both are eligible to do pg program in data science. To become a data scientist, you could earn a Bachelor's degree in Computer science, Social sciences, Physical sciences, and Statistics. You need to know programming languages like Python, Perl, C/C++, SQL, and Java.
2.What Are The Most Valuable Skill For a Data Science Professional ?
The most valuable skills for data science professionals are as follows:
- Probability & Statistics
- Multivariate Calculus & Linear Algebra
- Programming, Packages, and Software
- Data Wrangling
- Database Management
- Data Visualization
- Machine Learning / Deep Learning
- Cloud Computing
- Microsoft Excel
- DevOps
3. Is This Courses Useful For Non-Tt Professional
Any person with a structural thought process, good logical thinking skills, conviction towards learning new tools, and with a good business perspective can get into the field of data sciences. It’s not exceptional coders or highly knowledgeable people that are required.
4. What Is The Average salary Of a Data Scientist
The salary depends upon the company you are entering. The average data scientist’s salary is ₹698,412. As your experience and skills grow, your earnings rise dramatically as senior-level data scientists around more than ₹1,700,000 a year in India!
5. What Are The Top Algorithms That Every Data Science Professional Must Know
The top algorithms are:
- Decision Tree
- Logistic Regression
- Linear Regression
- SVM (Support Vector Machine) ...
- Naive Bayes
- KNN
- K-Means Clustering
- Random Forest
- Dimensionality Reduction Algorithms
- Neural Network
6. How Much Math In Statistics Is Used In Data Science
Math and Statistics for Data Science are essential because these disciples form the basic foundation of all the Machine Learning Algorithms. But, practical data science doesn't require very much math at all. It only requires skill in using the right tools. In statistics, you should know about probability distributions, statistical significance, hypothesis testing, and regression.
7. Which Programming Language Is Most Widely Used For Data Science
Python is the most popular and widely used data science programming language in the world today. It is an open-source, easy-to-use language that has been around. This general-purpose and vibrant language is innately object-oriented. It also ropes numerous paradigms, from functional to structured and procedural programming.
8.What Are The Top Companies In India To Work For After Completing Data Science Course
Many companies in India recruit Data Science professionals from entry-level to higher positions. Some of the top recruiters of Data Science and Big Data professionals in India for which you can work after completing the data science course are Equifax, Accenture, Amazon, Deloitte, LinkedIn, MuSigma, Flipkart, IBM, Citrix, Myntra, Juniper Network, etc
9. Do We Get Placement Support After Completing The Course
Yes, Madrid Software Trainings provide 100% placement support after the course and don’t throw at the deep end!
10.Do We Get Online Training Also In Data Science From Madrid Software Trainings
Yes, Madrid Software Trainings also provides online training for data science.
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