Full Stack Data Science & AI Program?
In today’s data-driven world, organizations are constantly seekingskilled professionals who can harness the power of data and artificialintelligence to drive business growth and innovation. A job-orientedprogram in Data Science and AI is designed to equip individuals withthe knowledge and skills required to excel in these high-demand fields.This program focuses on practical, real-world applications, ensuringgraduates are well-prepared for the workforce.
A job-oriented program in Data Science and AI is an excellent choice forindividuals looking to build a successful career in high-growth, high-impact fields. By gaining hands-on experience, industry knowledge, andpractical skills, graduates are well-positioned to meet the demands ofthe data-centric job market and drive innovation in their chosenindustries.
Data Science & AI Full Stack Training
| Track | Week Days | Weekends | Fast Track |
|---|---|---|---|
| Course Duration | 160 - 180 Days | 30 Weekends | 25 Days |
| Hours | 1 Hrs. Per Day | 2 Hrs. Per Day | 6+ Hrs. Per Day |
| Training Mode | Classroom/Online | Classroom/Online | Classroom/Online |
About Instructor :
Real Time Expert
Course Price at :
₹19,999 ₹25,000
Full Stack Data Science
- Undergraduate and graduate students studying computer science, statistics, mathematics, engineering, or related fields can incorporate data science into their academic pursuits.
- Software developers, programmers, and IT professionals can expand their skill set by learning data science to handle and analyze large datasets, implement machine learning algorithms, and derive insights from data.
- Healthcare professionals, including doctors, nurses, and researchers, can apply data science to analyze patient data, conduct medical research, and enhance healthcare outcomes.
- Individuals looking to make a career change can learn data science to enter a rapidly growing and in-demand field. Many online courses and bootcamps are designed to facilitate such transitions.
- Educators and researchers in academic institutions can integrate data science into their teaching and research activities, fostering a data-driven mindset among students.
Tsofttech was established to inform people about the newest technological developments, as the field of technology advances and people must stay up to date to compete in the market. We offer a group of instructors who will give you a comprehensive understanding of the specific technical courses you are interested in.
This is not the end of our job. The chance to work on real-time projects under the supervision of our real-time trainers is provided by Tsofttech. A technical back end team will always be ready to respond to your questions at any time and will help you make arrangements.
Data Science AI Full Stack Training?
Tsofttech is the top training facility for Data Science AI Full Stack Training, offering corporate instruction to several well-known businesses. Every session in the Data Science with AI Full Stack Training uses real-world examples and scenarios to impart lessons. We offer real-time assistance with job market information, resume preparation, interview preparation, problem-solving techniques for projects in the workplace, and approach to the job market.
Tsofttech offers Data Science Full Stack Classroom Training in Hyderabad as well as remote learning from any location. We offer all course recordings, materials, resume samples, and other pertinent information. We offer Online Data Science Full Stack Training in many countries, including South Africa, Sweden, Malaysia, Singapore, USA, Japan, and India. Tsofttech offers corporate training globally based on the needs of the company requirements with well experience real time experts.
Full Stack Data Science AI Course
- Introduction to DataScience
- Discussion on Course Curriculum
- Introduction to Programming
- Data types and type conversion Variables
- Flow Control : If, Elif, Else
- Data Structures, Indexing, SlicingIf,Else&For Loop & ,While loops
- List, List of Lists and List Comprehension Set and Tuple
- Dictionary and Dictionary comprehension
- Functions and Anonymous
- Functions Map, Reduce, Filter
- Error / Exception Handling
- File Handling
- Docstrings: Debugging, Modules and packages, OOPS, Installation
- Basics of DBMS
- Basics of SQL
- SELECT WHERE
- Statements
- JOINS
- Numpy
- Pandas
- Data Visualization
- Library : Matplotlib, Seaborn
- Descriptive Statistics : Central Tendency
- Variance , Standard Deviation Covariance
- Perason's and Spearman Correlation Coefficients
- Different types of Plots for Continuous,
- Different types of Distributions
Percentiles & quartiles, 5 numbersummary
- Population and Sample
Sampling Distribution and CentralLimit Theorem - Standard Error Confidence Interval
- Hypothesistesting : Onetail, Twotail and p-value
- Z-test, t-test, F-test, chisquare test
- Installations of Power BI and Tableau
- Basics of Power BI and Tableau
- Creating Visualization using Power BI
- Introduction one, two practical dataset
- Missing values treatment
- Outlier detection and treatment Plotting(univariate, bi-variate)
- Column Standardization
- Treating Categorical Variable
- Variable Creation and Transformation
- Understanding Feature Importanceconceptually
- Types of Machine Learning Methods
- Classification problem in general
- Different types of metrics for Classification
- Curse of dimensionality
- Feature Transformations
- Feature Selection
- Imbalanced Dataset and its effect on Bias Variance Tradeoff
- Overfitting vs Underfitting vs Normalfitting
- Linear Regression and It's assumptions
- L1L2 Regularization
- Forward and Backward selection methods
- Logistic Regression
- k-Nearest Neighbor classifier
- Naive Bayes classifier
- Decision Tree
- Support Vector Machine
- Ensemble : Bagging
- Random Forest Regressor andClassifier
- Ensemble : Boosting
- Gradient Boosting : AdaBoost XG Boost
- Gradient Descent technique
- Creating your own Ensemble Classifier
- Recommendation Engine
- Basics of Clustering : ClusteringMetrics, KMeans Algorithm
- Density Based Clustering DBSCAN
- Hierarchical Clustering :Agglomerative
- Market Basket Analysis
- Unsupervisedmetrics
- Principal Component Analysis
- Singualr Value Decomposition
- Population and Sample
- Sampling Distribution and Central
- Limit Theorem
- Standard Error
- Confidence Interval
- Hypothesistesting : Onetail, Twotailand p-value
- Z-test, t-test, F-test, chisquare test
- Regularization
- Optmizers
- Hyper parameter sand tuning ofthe same
- Convolution alNeuralNetworks(CNN)
- Project : Image Classification
- Different types of CNNarchitectures
- Texts, Tokens
- Bag of Words
- Basic text classification based on Bagof Words
- n-gram : Unigram, Bigram
- Word vectorizer basics, One HotEncoding
- Count Vectorizer
- Word cloud and gensim
- TF-IDFVectorizer
- Word 2VecandGlove
- Text classification using
- Word2VecandGlove
- Recurrent Neural Network(RNN)
- Back Propagation through time
- Different types of RNN:LSTM,GRU
- Biirectional RNN
- Seq2Seqmodel(EncoderDecoder)
- BERT Transformers
- Textgeneration and classification using Deep
- Generative-AI(Chat-GPT)
- Different Components of Time Series
- Statistical Models of time series for ecasting AR
- Time Series Forecasting using Statsmodel library
- Time Series Forecasting using DeepLearning
- Pyspark Installation and working onbasic code
- Data bricks
- Hadoop
- Resume/Profile Building
- Mock Interviews
- Career Mentoring
Full Stack Data Science AI
Hands-On Learning
Engage in hands-on learning through interactive activities, simulations, and practical exercises to deepen your understanding and enhance your skills.
Guest Lecturer and Industry Experts
Enrich your education with insights from guest lecturers and industry experts who bring real-world experience to the classroom.
Online Learning Resources
Access a plethora of online learning resources to expand your knowledge, ranging from interactive courses and video lectures to e-books and virtual labs.
Resume Preparation
Craft a compelling resume showcasing your skills, experience, and accomplishments to effectively communicate your professional value and stand out to potential employers.
Individual Mock Interviews by Real Time Experts
Sharpen your interview skills through individual mock interviews conducted by real-time experts, gaining valuable insights and constructive feedback to excel in your professional job search.
Job Placement Support
Receive comprehensive job placement support to navigate the employment landscape successfully, including personalized guidance, networking opportunities, and resources to secure fulfilling career opportunities.
FAQs?
Real-time classroom and online sessions provide direct communication with the trainers. During the sessions, students are encouraged to ask questions and get all of their doubts answered.
Yes, we will offer training resources and guidelines to aid in more effective learning of the subject. There is also an assignment and notes available to work on real-world scenarios.
We are an extremely cost-effective training facility offering top-notch instruction at incredibly low and competitive prices.
Indeed, remote attendance is particularly integrated into online classrooms. Users of online programs can access the classroom from any location as long as they have a strong internet connection.
Yes, we help candidates get employment after they successfully finish and receive certification in the course in which they registered.