Machine Learning Course Training in Hyderabad
Give your career the ultimate boost with Codegnan’s elaborate Machine Learning course in Hyderabad. We are a premium machine learning training institute in Hyderabad with a proven track record of student success.
- Get a 360 degree perspective of the latest ML and Python trends
- End-to-end training with real-time projects
- Educators with 5+ years of industry experience
- 1.2k+ students hired till date
- Trusted by 4k+ students all over India
- English
- 1 Month
- 7,999
Become a Machine Learning developer
Talk to our expert Machine Learning mentors and learn how our training programs in Hyderabad can help you become a Machine Learning developer and get a high-paying job.
300 Hours Instructor
Led Training
Self-Paced
Videos
Exercises
& Projects
Authorized
Certification
Flexible
Schedule
Lifetime Access
& Upgrade
24/7 Lifetime
Support
Overview and Key Features of Machine Learning Course in Hyderabad
Our 60 hours machine learning certification offers students a comprehensive knowledge of machine learning algorithms and techniques by developing their analytical abilities and statistical thinking with real-time case studies. By the end of the course, they will be able to develop the practical skills for building, evaluating, and deploying ML models in different corporate settings.
- Core curriculum delivered by industry experts
- Online Python sessions included
- Firsthand training on live projects
- Online and offline classes available
Career Scope for Machine Learning in Hyderabad
Machine learning has emerged as one of the highest paying professions in the global technology sector. With a number of prominent tech giants established in Hyderabad, the city generates lucrative job opportunities in domains of AI, ML and data analytics every year.
1. Booming Software Industry
Hyderabad is a home to the largest campuses of renowned software companies including Google, Microsoft, Facebook and Apple. Apart from this, the city has seen a surge in technology startups in the last few years, making it a great choice for people looking to build or transition their career to machine learning.
2. Wide Range of Industry Applications
Versatility is the beauty of machine learning. As the field aids directly to the growth of an organization, companies from a variety of sectors including healthcare, agriculture, finance, and e-commerce are using it. So even if you don’t have a prior background in IT, with just a little training, you can become an expert ML professional in your area of expertise.
3. High Job Availability
In recent years, machine learning has surfaced as the most promising profession with an average growth rate of more than 340% on a year-on-year basis. Getting advanced training in ML will open doors to a variety of jobs including AI/ML engineer, ML architect, NLP engineer, ML data scientist and AI/ML developer.
4. Demand for Machine Learning Engineers
The demand for machine learning engineers in Hyderabad has seen a massive growth. The city alone had witnessed more than 3,500 job openings in the AI, ML and deep learning fields in the last three months, making it one of the hottest jobs of the decade. If you want to learn machine learning in Hyderabad, now is the right time.
5. Salary in Hyderabad for Machine Learning
The average salary of a Machine Learning Engineer in Hyderabad is estimated at ₹ 9.1 Lakhs per annum, with the yearly payout ranging from ₹ 3.0 Lakhs to ₹ 18.0 Lakhs. The monthly salary of a ML engineer on the other hand ranges between ₹ 45k to ₹ 47k.
Machine Learning course curriculum in Hyderabad
1. Importance of Data in 21st Century
2. Types of Data and its usage
3. Python Crash course (using IDLE)
● Data Types
● Conditional Statements
● Control Statements
● Functions
4. What is Machine Learning and types of Learning
5. Anaconda Environment Setup and its usage .
1. Numpy
● Creating arrays, Difference between List and Array
● Accessing Elements, Slicing, Concatenation
● Universal Functions, Shape Manipulation
● Automatic Reshaping, Vector Stacking.
2. Pandas
● Pandas DataStructures
● Indexing, Selecting Data, Slicing functions
● Some Useful DataFrame Functions
● Handling Missing Values in DataFrame
● Time Series Analysis
3. Data Visualization Libraries
● Matplotlib
● Plotly
● Basic Plotting with Seaborn
● Projects on Data Analysis – Google Analysis, Market Analysis
4. Sklearn usage
● Playing with Scikit-learn, Understanding classes in Scikit-learn
Machine Learning Fundamentals
• What is machine learning?
• How Machine Learning works?
• Applications of machine learning
• Different types of machine learning
• How do we know machines are learning right?
• Different stages of machine learning projects.Data Transformation and Preprocessing
• Handling Numeric Features
• Feature Scaling
• Standardization and Normalization
• Handling Categorical Features
• One Hot Encoding, pandas get_dummies
• Label Encoding
• More on different encoding techniquesTrain,Test and Validation Split
• Simple Train and Test Split
• Drawbacks of train and test split
• K-fold cross validation
• Time based splittingOverfitting And Underfitting
• What is overfitting ?
• What causes overfitting?
• What is Underfitting ?
• What causes underfitting ?
• What are bias and Variance ?
• How to overcome overfitting and underfitting problems ?
Regression
• Introduction to Linear Regression
• Understanding How Linear Regression Works
• Maths behind Linear Regression
• Ordinary Least Square
• Gradient Descent
• R – square
• Adjusted R-square
• Polynomial Regression
• Multiple Regression
• Performance Measures – MSE, RMSE, MAE
• Assumption of Linear Regression
• Ridge and Lasso regression
• RFE (Recursive Feature elimination)
Hands On – Problem formulation and Case Study on Hotstar, Netflix, And housing prices Dataset
Classification
Logistic regression
• Introduction to classification problems
• Introduction to logistic regression
• Why the name regression ?
• The sigmoid function
• Log odds
• Cost function
• Feature importance and model interpretability
• Collinearity of features
• Feature engineering for non-linearly separable data
Performance Metrics for Classification Algorithms
• Accuracy Score
• Confusion Matrix
• TPR, FPR, FNR, TNR
• Precision – Recall
• F1-Score
• ROC Curve and AUC
• Log LossHands On – Real World Case Study on IBM HR Employee Attrition datasetK Nearest Neighbors
• Introduction to KNN
• Effectiveness of KNN
• Distance Metrics
• Accuracy of KNN
• Effect of outlier on KNN
• Finding the k Value
• KNN on regression
• Where not to use KNN
Hands On – Different case study on KNN
Natural Language Processing
• Introduction to NLP
• Converting Text to vector
• Data Cleaning
• Preprocessing Text Data – Stop word removal, Stemming , Tokenization, Lemmatization
• Collecting Data from the web
• Developing a Classifier
• Building Pipelines for NLP projects
• Uni-grams,bi-grams and n-grams
• tf-idf
• Word2Vec
Hands On – Text Summarization, WebScraping for data, Sentiment Analysis, Topic Modelling, Text Summarization and Text Generation
Naive Bayes
• Refresher on conditional Probability
• Bayes Theorem
• Examples on Bayes theorem
• Exercise problems on Naive Bayes
• Naive Bayes Algorithm
• Assumptions of Naive Bayes Algorithm
• Laplace Smoothing
• Naive Bayes for Multiclass classification
• Handling numeric features using Naive Bayes
• Measuring performance of Naive Bayes
Hands On – Working on spam detection and Amazon Food Review dataset
Support Vector Machines
• Introduction to SVM
• What are hyperplanes ?
• Geometric intuition
• Maths behind svm’
• Loss Function
• Kernel trick
• Polynomial kernel, rbf and linear kernels
• SVM Regression
• Tuning the parameter
• GridSearch and RandomizedSearch
• SVM Regression
Hands On – Case Study SVM on Social network ADs and Gender recognition from voice datasetDecision Tree
• Introduction to Decision Tree
• Homogeneity and Entropy
• Gini Index
• Information Gain
• Advantages of Decision Tree
• Preventing Overfitting
• Advantages And Disadvantages
• Plotting Decision Trees
• Plotting feature importance
• Regression using Decision Trees
Hands-On – Decision Tree on US Adult income dataset
Ensemble Learning
• Introduction to Ensemble Learning
• Bagging (Bootstrap Aggregation)
• Constructing random forests
• Runtime
• Case study on Bagging
• Tuning hyperparameters of random forest(GridSearch, RandomizedSearch)
• Measuring model performance
• Boosting
• Gradient Boosting
• Adaboost and XGBoost
• Case study on boosting trees
• Hyperparameter tuning
• Evaluating performance
• Stacking Models
Hands-On – Talking Data Ad Tracking Fraud Detection case study
Clustering
• Introduction to unsupervised learning
• Applications of Unsupervised Learning
• Kmeans Geometric intuition
• Maths Behind Kmeans
• Kmeans in presence of outliers
• Kmeans random initialization problem
• Kmeans++
• Determining the right k
• Evaluation metrics for Kmeans
• Case study on Kmeans
• Hierarchical Clustering
• Agglomerative and Divisive
• Denodgrams
• Case study on hierarchical clustering
• Segmentation
• Case Study on Segmentation
• DBSCAN – Density based clustering
• MinPts and Eps
• Core Border and Noise Points
• Advantages and Limitation of DBSCAN
• Case Study on DBSCAN clustering
Hands On – Applying Unsupervised models on Retail data and mall customer datasetDimensionality Reduction Techniques
• What are dimensions?
• Why is high dimensionality a problem ?
• Introduction to MNIST dataset with (784 Dimensions)
• Into to Dimensionality reduction techniques
• PCA (Principal Component Analysis) for dimensionality reduction
• t-sne (t-distributed stochastic neighbor embeddingHands-on: Applying Dimensionality Reduction on MNIST data
• Introduction
• Markov Decision Process
• Expected Return
• Policy and Value Function
• Q-Learning
• Exploration vs Exploitation
• OpenAI Gym and python for Q-learning
• Training Q-Learning Agent
• Watching Q-Learning Play GamesHands On – Working with OpenAI Gym and Q-Learning
Tools You Will Learn with Our Machine Learning Course in Hyderabad
Through our well devised course, you will be able to kickstart your machine learning and AI career with contemporary tools and technologies including Python, Numpy, Pandas, Matplotlib, Jupyter, Seaborn, Anaconda, Flask and scikit-learn. You will also get a chance to solve exciting challenges and showcase your certification on our HackerRank platforms.
Become a Machine Learning developer
Talk to our expert Machine Learning mentors and learn how our training programs in Hyderabad can help you become a Machine Learning developer and get a high-paying job.
Machine Learning Projects You Will Work On
At Codegnan, we allow students to engage in industry projects to help them get a taste of what real world problems actually look like. Our goal is to help you make the best use of your potential. Here are the three machine learning projects you will work on:
1. Real Time Rain Prediction
Students will learn how to fetch and preprocess live data, install necessary libraries, obtain an API key, and successfully train and deploy a machine learning model. They will be equipped with vital skills in collection, data cleaning, model building, evaluation, and many more.
2. Stock Price Prediction
This hands-on project helps students work on stock price data assimilation and prediction. The core competencies included are exploring and visualizing data, feature engineering, ML algorithm selection, data splitting and analysis.
3. House Price Prediction
Get the best out of machine learning and data analytics with the real time project on predicting price of houses from a reliable source. The goal of the project is to teach students the complexities of web scraping, data scraping, model fine-tuning, and updating and retraining the model among others.
Who is This Machine Learning Course For?
Codegnan’s machine learning course in Hyderabad is for all those tech savvy people who want to become a part of the global machine learning army and bring about cutting edge AI developments. We ensure that you get enlightened with machine learning and Python problem solving in the most efficient ways. Our course is perfect for:
1. College students/ fresh graduates
The curriculum is easy-to-understand, making it suitable for college students and fresh graduates who don’t hold much experience in technical areas like machine learning, data analysis and AI.
2. Beginner developers/ engineers
The classes are held in a highly interactive environment to help beginners clarify their doubts and queries by connecting with experienced students and industry experts all over the world.
3. IT professionals
Professionals in the information technology and software industries can upskill themselves with the latest skills and abilities in the machine learning landscape by working on actual time case studies and projects.
4. Practically anyone interested in machine learning
You don’t necessarily need to have a degree in computer science, IT, statistics or any related area. Our course is structured to suit the needs of all programming and math enthusiasts. All you need to bring is a curiosity to learn.
What You Will Learn with Our Machine Learning Training Classes in Hyderabad
- Gain practical experience in machine learning algorithms, natural language processing techniques, neural networks and support vector machines
- Become an expert in exploratory data analysis using Numpy and Pandas
- Experiential learning in regression, web scraping, data engineering and preprocessing, and supervised and unsupervised learning
- Learn to uncover insights, detect patterns, and make accurate predictions from balanced and imbalanced datasets with extensive Python training
- Acquire competence in finding optimal solutions to actual time business problems with data analytics and machine learning
Machine Learning Course Certification in Hyderabad
Codegnan offers students an opportunity to receive globally recognized certification upon completion of the course. Our job assists have helped students get hired by topmost organizations including SAP, Amazon, EY, Teksan, Cognizant, TCS, Wipro, Temenos and so many more.
We not only prepare our students to be subject experts. We train them to be top professionals.
Meet Your Machine Learning Course Trainers
Manohar Chary Vadla
Manohar Chary Vadla is a Data Scientist and Mentor with a Bachelor of Commerce in Computer Science background, having 2+ years of hands-on experience in Data Extraction from documents using Python and deep learning techniques.
His areas of expertise include research and implementation in machine learning and deep learning, such as regression, classification, neural networks, and natural language processing (NLP).
As part of the AI-for India Event, in collaboration with GUVI Geek Networks and IITM Research Park, he developed a facial recognition application using the Python programming language.
Codegnan Learners success
1250+ Companies Have Hired Codegnan Learners
Machine Learning Course Training Fees in Hyderabad— Get Highest ROI
We, at Codenan, ensure that our students get premium quality learning at a budget that suits their pockets. Our carefully designed 1-month training course is priced at a cost-effective rate of ₹ 10,000. However, codegnan is currently offering the course only for ₹7,999 for a limited time. Not only will you be able to gain a myriad of lifetime skills, but you will also be well prepared to bag some of the most high-paying positions in the machine learning industry.
Machine Learning Course in Hyderabad FAQs
1. What is the eligibility criteria for the machine learning course of Codegnan?
There are no criteria for enrolling in the course. You can be a school or college student, a fresher or a professional, this one size fits all type of certification program is suited for all.
2. What are the fees of the machine learning course offered by codegnan?
Codegnan offers 60 hours of learning which includes placement assistance with more than 50 hours of instructor-led training at only ₹ 10,000. Currently, get our machine learning training program only for ₹7,999.
3. What certification will I receive upon completion of the course?
You will receive an industry recognized machine learning course completion certificate by Codegnan.
4. What is the duration of this machine learning course in Hyderabad?
This machine learning course in Hyderabad has a duration of 1 month, with the timeline being the same for both online and offline modes.
5. Are there any prerequisites of this Machine Learning course in Hyderabad?
There are only two prerequisites for the course – a knack for AI, and a desire to transform your career. Apart from that, nothing is required from a candidate’s end.
6. Is this course suitable for a person from a non-technical background?
Yes, even people from non-technical backgrounds including management, arts, or any other non-computer related field can enroll in the course. The curriculum is designed to be easily understood by candidates of any academic and professional expertise.
7. What are the job opportunities after this machine learning course from Codegnan?
After completing Codegnan’s machine learning course in Hyderabad, one can build a career in AI, ML, data science or similar fields. AI/ML engineer, ML architect, NLP engineer, ML data scientist and AI/ML developer are some of the most notable professions our students have been hired in.
8. Is Python necessary for machine learning?
Python is not necessarily needed for machine learning. However, it is hands down the most popular programming language as far as machine learning is concerned. Python is consistent and simple, that’s why most of the companies use it.
9. Can I learn machine learning in 6 months?
Yes, you can learn machine learning in 6 months. In this duration, you will easily grasp basic and intermediate level ML tools and techniques which you can later apply to your own projects.
10. Does codegnan offer online and classroom training for machine learning courses in Hyderabad?
Codegnan offers its machine learning course both online and offline. Enrolled students have an opportunity to engage in live classes from top industry professionals, and complete their projects in a real classroom.
11. What if I have queries after the course?
We will assist you in case of any queries, even after the completion of your Java online training. You are always welcome to reach through our customer care number or email us your query. We would love to assist you.
12. What is meant by 24*7 lifetime support?
You will get 24*7 support and lifetime access to the LMS, where course material like presentations, installation guides & class recordings are available. Email support will always be there to clear your doubts.