Login
Congrats in choosing to up-skill for your bright career! Please share correct details.
Home / Data Science & Deep Learning / Professional Data Science & AI Course in Calicut
INR 1,46,438 94,100+Tax
This dual certification program in Data Science and AI firmly reinforces concepts in mathematics, statistics, calculus, linear algebra, and probability. A primer on Data Mining and the use of Regression Analysis methods in Data Mining ensues. The concepts and deployment of Python programming to enable Data Mining, Machine learning are also dealt with in detail. The use of NLP libraries and OpenCV to code machine learning algorithms are detailed. The main highlight of this course is the focus on machine learning, deep learning, and neural networks. Feedforward and backward propagation in neural networks are described at length. The deployment of Activation function, Loss function, non- linear activation function is elaborated. A thorough analysis of Convolution Neural Networks (CNNs), Recurrent Neural Networks (RNNs), GANs, Reinforcement Learning, and Q learning is also facilitated in this course. This course is a comprehensive package for all IT enthusiasts who wish to design and develop AI applications in their field of study. Data Science and Artificial Intelligence? Data Science is related to analyzing, processing, and maintaining data sets. It aims at data modeling and data warehousing to trace the uncontrollably growing data set reaching the organizational goals. Artificial intelligence is the emerging technology used in machines to execute at reasoning by cloning human intelligence. With the aid of Deep learning and Natural language processing, AI technologists enable machines in identifying inferences and patterns. Artificial Intelligence automation has become easy and the development of Intelligent products is possible. Our Data Science and Artificial Intelligence certification program in Salem will help you in obtaining extensive knowledge and prepares you to be settled in high paid jobs.
The present market is all about the data. To get into this, there is a vital requirement for skilled Data Science and AI professionals. There is enormous scope for a lucrative career in this domain. By using the cutting edge and appropriate tools the freshers and professionals will be able to build algorithms and analyze huge data. By using the opportunity of individual attention given by experts at 360DigiTMG, the students will be adequately trained and will be able to understand the course very effectively. Students will be exposed to real-time projects, at the learning level only they are prepared to face the challenges that are inclined to be in industries. Data Science and AI are not confined to a specific industry, so the professionals in data science and Artificial Intelligence will have the liberty to work in the areas of their interest. The main areas where Data Science and Artificial Intelligence professionals are in demand are Medicine, Space, Robotics, Automation, Marketing, Information management, Military activities, and many more. The primary objective of Data Science and Artificial training at 360DigiTMG is to deliver skilled professionals by providing quality training, guiding them to implement and gain hands-on experience.
Learn about insights on how data is assisting organizations to make informed data-driven decisions. Gathering the details about the problem statement would be the first step of the project. Learn the know-how of the Business understanding stage. Deep dive into the finer aspects of the management methodology to learn about objectives, constraints, success criteria, and the project charter. The essential task of understanding business Data and its characteristics is to help you plan for the upcoming stages of development. Check out the CRISP - Business Understanding here.
In this module, you will learn about dealing with the Data after the Collection. Learn to extract meaningful information about Data by performing Uni-variate analysis which is the preliminary step to churn the data. The task is also called Descriptive Analytics or also known as exploratory data analysis. In this module, you also are introduced to statistical calculations which are used to derive information along with Visualizations to show the information in graphs/plots
The raw Data collected from different sources may have different formats, values, shapes, or characteristics. Cleansing, or Data Preparation, Data Munging, Data Wrapping, etc., are the next steps in the Data handling stage. The objective of this stage is to transform the Data into an easily consumable format for the next stages of development.
Learn the preliminaries of the Mathematical / Statistical concepts which are the foundation of techniques used for churning the Data. You will revise the primary academic concepts of foundational mathematics and Linear Algebra basics. In this module, you will understand the importance of Data Optimization concepts in Machine Learning development. Check out the Mathematical Foundations here.
Data mining unsupervised techniques are used as EDA techniques to derive insights from the business data. In this first module of unsupervised learning, get introduced to clustering algorithms. Learn about different approaches for data segregation to create homogeneous groups of data. In hierarchical clustering, K means clustering is the most used clustering algorithm. Understand the different mathematical approaches to perform data segregation. Also, learn about variations in K-means clustering like K-medoids, and K-mode techniques, and learn to handle large data sets using the CLARA technique.
Dimension Reduction (PCA and SVD) / Factor Analysis Description: Learn to handle high dimensional data. The performance will be hit when the data has a high number of dimensions and machine learning techniques training becomes very complex, as part of this module you will learn to apply data reduction techniques without any variable deletion. Learn the advantages of dimensional reduction techniques. Also, learn about yet another technique called Factor Analysis.
Learn to measure the relationship between entities. Bundle offers are defined based on this measure of dependency between products. Understand the metrics Support, Confidence, and Lift used to define the rules with the help of the Apriori algorithm. Learn the pros and cons of each of the metrics used in Association rules.
The study of a network with quantifiable values is known as network analytics. The vertex and edge are the nodes and connection of a network, learn about the statistics used to calculate the value of each node in the network. You will also learn about the google page ranking algorithm as part of this module.
Learn to analyse unstructured textual data to derive meaningful insights. Understand the language quirks to perform data cleansing, extract features using a bag of words and construct the key-value pair matrix called DTM. Learn to understand the sentiment of customers from their feedback to take appropriate actions. Advanced concepts of text mining will also be discussed which help to interpret the context of the raw text data. Topic models using LDA algorithm, emotion mining using lexicons are discussed as part of NLP module.
Revise Bayes theorem to develop a classification technique for Machine learning. In this tutorial, you will learn about joint probability and its applications. Learn how to predict whether an incoming email is spam or a ham email. Learn about Bayesian probability and its applications in solving complex business problems.
k Nearest Neighbor algorithm is a distance-based machine learning algorithm. Learn to classify the dependent variable using the appropriate k value. The KNN Classifier also known as a lazy learner is a very popular algorithm and one of the easiest for application.
In this tutorial, you will learn in detail about the continuous probability distribution. Understand the properties of a continuous random variable and its distribution under normal conditions. To identify the properties of a continuous random variable, statisticians have defined a variable as a standard, learning the properties of the standard variable and its distribution. You will learn to check if a continuous random variable is following normal distribution using a normal Q-Q plot. Learn the science behind the estimation of value for a population using sample data.
Learn to frame business statements by making assumptions. Understand how to perform testing of these assumptions to make decisions for business problems. Learn about different types of Hypothesis testing and its statistics. You will learn the different conditions of the Hypothesis table, namely Null Hypothesis, Alternative hypothesis, Type I error, and Type II error. The prerequisites for conducting a Hypothesis test, and interpretation of the results will be discussed in this module.
Data Mining supervised learning is all about making predictions for an unknown dependent variable using mathematical equations explaining the relationship with independent variables. Revisit the school math with the equation of a straight line. Learn about the components of Linear Regression with the equation of the regression line. Get introduced to Linear Regression analysis with a use case for the prediction of a continuous dependent variable. Understand about ordinary least squares technique.
In the continuation of the Regression analysis study, you will learn how to deal with multiple independent variables affecting the dependent variable. Learn about the conditions and assumptions to perform linear regression analysis and the workarounds used to follow the conditions. Understand the steps required to perform the evaluation of the model and to improvise the prediction accuracies. You will be introduced to concepts of variance and bias.
You have learned about predicting a continuous dependent variable. As part of this module, you will continue to learn Regression techniques applied to predict attribute Data. Learn about the principles of the logistic regression model, understand the sigmoid curve, and the usage of cut-off value to interpret the probable outcome of the logistic regression model. Learn about the confusion matrix and its parameters to evaluate the outcome of the prediction model. Also, learn about maximum likelihood estimation.
Learn about overfitting and underfitting conditions for prediction models developed. We need to strike the right balance between overfitting and underfitting, learn about regularization techniques L1 norm and L2 norm used to reduce these abnormal conditions. The regression techniques of Lasso and Ridge techniques are discussed in this module.
Extension to logistic regression We have multinomial and Ordinal Logistic regression techniques used to predict multiple categorical outcomes. Understand the concept of multi-logit equations, baseline, and making classifications using probability outcomes. Learn about handling multiple categories in output variables including nominal as well as ordinal data.
As part of this module, you learn further different regression techniques used for predicting discrete data. These regression techniques are used to analyze the numeric data known as count data. Based on the discrete probability distributions namely Poisson, negative binomial distribution the regression models try to fit the data to these distributions. Alternatively, when excessive zeros exist in the dependent variable, zero-inflated models are preferred, you will learn the types of zero-inflated models used to fit excessive zeros data.
Support Vector Machines / Large-Margin / Max-Margin Classifier
Kaplan Meier method and life tables are used to estimate the time before the event occurs. Survival analysis is about analyzing the duration of time before the event. Real-time applications of survival analysis in customer churn, medical sciences, and other sectors are discussed as part of this module. Learn how survival analysis techniques can be used to understand the effect of the features on the event using the Kaplan-Meier survival plot.
Decision Tree models are some of the most powerful classifier algorithms based on classification rules. In this tutorial, you will learn about deriving the rules for classifying the dependent variable by constructing the best tree using statistical measures to capture the information from each of the attributes.
Learn about improving the reliability and accuracy of decision tree models using ensemble techniques. Bagging and Boosting are the go-to techniques in ensemble techniques. The parallel and sequential approaches taken in Bagging and Boosting methods are discussed in this module. Random forest is yet another ensemble technique constructed using multiple Decision trees and the outcome is drawn from the aggregating the results obtained from these combinations of trees. The Boosting algorithms AdaBoost and Extreme Gradient Boosting are discussed as part of this continuation module. You will also learn about stacking methods. Learn about these algorithms which are providing unprecedented accuracy and helping many aspiring data scientists win first place in various competitions such as Kaggle, CrowdAnalytix, etc.
Time series analysis is performed on the data which is collected with respect to time. The response variable is affected by time. Understand the time series components, Level, Trend, Seasonality, Noise, and methods to identify them in a time series data. The different forecasting methods available to handle the estimation of the response variable based on the condition of whether the past is equal to the future or not will be introduced in this module. In this first module of forecasting, you will learn the application of Model-based forecasting techniques.
In this continuation module of forecasting learn about data-driven forecasting techniques. Learn about ARMA and ARIMA models which combine model-based and data-driven techniques. Understand the smoothing techniques and variations of these techniques. Get introduced to the concept of de-trending and de-seasonalize the data to make it stationary. You will learn about seasonal index calculations which are used to re-seasonalize the result obtained by smoothing models.
Call us Today!
+91 9989994319
Limited seats available. Book now
Alumni Speak
"The training was organised properly, and our instructor was extremely conceptually sound. I enjoyed the interview preparation, and 360DigiTMG is to credit for my successful placement.”
Pavan Satya
Senior Software Engineer
"Although data sciences is a complex field, the course made it seem quite straightforward to me. This course's readings and tests were fantastic. This teacher was really beneficial. This university offers a wealth of information."
Chetan Reddy
Data Scientist
"The course's material and infrastructure are reliable. The majority of the time, they keep an eye on us. They actually assisted me in getting a job. I appreciated their help with placement. Excellent institution.”
Santosh Kumar
Business Intelligence Analyst
"Numerous advantages of the course. Thank you especially to my mentors. It feels wonderful to finally get to work.”
Kadar Nagole
"Excellent team and a good atmosphere. They truly did lead the way for me right away. My mentors are wonderful. The training materials are top-notch.”
Gowtham R
Data Engineer
"The instructors improved the sessions' interactivity and communicated well. The course has been fantastic.”
Wan Muhamad Taufik
Associate Data Scientist
"The instructors went above and beyond to allay our fears. They assigned us an enormous amount of work, including one very difficult live project. great location for studying.”
Venu Panjarla
AVP Technology
Our Alumni Work At
And more...
360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.
Student Voices
4.8
I've reached a major milestone in my Data Analytics internship with 360DigiTMG. With guidance from experienced mentors, they’ve really helped me get closer to reaching my goals. Embrace the valuable knowledge and skills gained and continue leveraging this opportunity to excel in the dynamic field of data analytics.
I'm Sai Manikanta, delighted to share my internship journey at 360DigiTMG. This internship has been a great opportunity for me to expand my limits and gain new skills. Diverse activities provided profound insights, shaping a promising future. Grateful for this opportunity, I eagerly anticipate forthcoming outcomes.
The data analytics program was truly outstanding! The meticulously structured classes and enthusiastic instructors made learning both enjoyable and engaging. With this extensive knowledge at my disposal, I am not only confident but also eager to make significant strides in the field of data analytics.
One of the best institutes for training in Hyderabad. I am done with the Data science and Machine Learning course here. Trainers are highly educational and instructive. Invaluable experience gained through live projects, enhancing technical familiarity. Additional value provided through helpful working sessions further enriches the learning journey.
The teacher and staff are highly skilled at their jobs. They teach in a way that's easy to understand and interesting. They know a lot about the subject, so learning from them is great. The teacher plans everything well and explains hard stuff with lots of examples using Excel.
It was a wonderful experience for me as an intern to work in 360digitmg. This internship had made me become an expert in the field of data analytics which had greatly motivated me and Working with real-time datasets provided invaluable experience, enhancing my skills significantly.
It was an awesome experience at 360Digitmg, offering the best resources and fostering excellent interaction. Working on real-life projects under expert supervision provided invaluable learning opportunities. Overall, it was a highly rewarding learning experience that contributed significantly to my growth and career advancement.
I found a great coaching institute in Chennai for data-related courses. I completed a successful data analytics program there. The trainers were skilled and supportive, especially Vijay, who made learning Python easy. Thanks to him and 360DigiTMG. I also learned Data Analytics with SQL, Tableau, and Excel.
360DigiTMG institute offers an exceptional learning experience, excelling in data science and machine learning. Despite lacking coding background, tutors ensured effective learning, making concepts easily understandable. Tutorial sessions covered job interview prep and case studies, with Mind maps boosting confidence. Highly recommend this Bangalore institute for data-related courses.
Excited for upcoming internships, confident in my improved skills from the program. Explored new territories and gained invaluable experience. Ready to apply newfound knowledge and continue growing in future opportunities. Grateful for the journey so far, eager for what's ahead.
360DigiTMG institute offers one place where the course curriculum is so good and teacher training, equipping students with skills for their dream job. Grateful for the internship experience, including live projects, resume building, presentation practice, and interview preparation sessions. Enhanced confidence for future interviews. Thank you, 360DigiTMG, for the invaluable learning journey.
The data analytics with python course in the best coaching centre in Chennai. Finished the course well and worked on practical tasks. This helped me build my professional experience. By participating in interview preparation and project presentation sessions, I realized that I could present myself confidently to an interview.
During my internship at 360DigiTMG, I gained invaluable experience, expanding my knowledge significantly. The opportunity provided a rich learning environment, fostering personal and professional growth. Grateful for the wonderful experience and the skills acquired, which will undoubtedly shape my future endeavours.
Great institute! Exceptional learning experience, especially in data science and machine learning. Tutors adeptly simplified complex concepts despite my coding limitations. Varied tutorial sessions prepared us for job interviews with insightful case studies. Mind maps boosted confidence. Highly recommend this Bangalore-based institute for data-related courses.
Class Schedule
Didn’t receive OTP? Resend
Let's Connect! Please share your details here