Data Science Training
1800+
10+
60 HrsData Science Training in Chennai at Credo Systemz provided by experienced Data Scientists. Our Data Science Course module is completely designed about how to analyze Big Data using R programming and Hadoop. Credo Systemz is the Best place to learn Data Science with Python Training in Chennai. Data Science course certification will help you be a professional Data Scientist. If you really Interested to Learn Best Data Science course in Chennai, then Credo Systemz is the Right place.
Our Best Data Science Training kick starts from statistics and insights of the large volume of data. So that we ranked as Best Data Science Training Institute in Chennai, Velachery. At the end of the course, you become a Data Scientist.
- Data analytics is the heartbeat of all top organizations
- Data Science is everywhere
- You become Decision-Making person
- Data Science is rapidly increasing than expected
- Offering new revenue strategies
Training from
Industrial Experts
24 x 7
Expert Support
Hands on
Practicals/ Projects
Certification
of Completion
100% Placement
Assistance
Free
Live Demo
What you will get in the Course?
- Machine Learning Algorithms /Supervised
- Linear Regression & Polynomial Regression
- Random Forest & Naïve Bayes
- SVM, GBM, Xgboost
- Clustering Algorithms/ Unsupervised Learning using K means
- Deep Learning using Keras Tensor Flow (MLP –Multi Layer perceptron)
- NLP Basics
- Tableau Basics
- Python
- Statistics
- H20.ai
Highlights of Data Science Training by Credo Systemz
- Credo Systemz is one of the most prominent Data Science training institutes that presents First Class Training in Chennai.
- Conducted Data Science Training with well Advanced Learning Program .
- Highly affordable Course Contents is updated by the domain Experts.
- Well Experienced Trainers who are working in leading Top MNCs.
- Shape your learning path with customized skills in Data Science.
- Flexible Class Time Scheduling with tailor-made fees Structure.
- Get Practical Knowledge with Real-time Hands-on Projects.
- Provided Certification and Job assistance at the end of the Course completion.
Course Features
- Duration60 hours
- Skill levelAll level
- Batch Strength15
- AssessmentsYes
- Mock InterviewsYes
- Resume BuildingYes
- PlacementsYes
- Flexible TimingYes
- Fee InstallmentsYes
- LanguageTamil/English
- Market trend of Data Science
- Opportunities for Data Science
- What is the need for Data Scientists
- What is Data science
- Data Science Venn Diagram
- Data Science Use cases
- Knowing the roles of a Data Science practitioner
- Data Science – Skills set
- Understanding the concepts & definitions of:
- Artificial Intelligence
- Machine Learning- Deep Learning
- NLP
- Computer Vision
- What is Business Intelligence?
- What is ETL?
- Layers of a Data Warehouse
- OLAP VS OLTP
- Facts and Dimensions
- Big Data tools and it’s uses
- Big Data stack
- Understanding Structured text Data
- Understanding Unstructured text Data
- Understanding Descriptive vs Predictive vs Prescriptive Analytics
- Difference between Analytics vs. Analysis
- Data Science Project Lifecycle
- Technology Stack Involved in the Lifecycle
- Machine Learning tools
- Development tools
- Languages
- Data Platforms
- CRISP - Cross-industry standard process for Data Mining
- 5WIH- The questions that kick start a ML project
- 80-20 Rule of Data Analytics
- Supervised Vs Unsupervised Learning
- Data Science- Use case bubble
- Data Mining techniques
- Data Wrangling or Data Munging
- Data Categorization basics
- Different Types of Data
- Types of Data Collection
- Data Sources
- Data Collection plan
- Data Quality Issues
- Types of Data Error
- Ration Scale Vs Interval Scale
- Predictors/Features vs Predictions/Labels
- Understanding Imbalance in Data
- What is Statistics
- Sample Vs Population
- Measure of Central vs Dispersion
- Frequency Distribution
- Cumulative Frequency Distribution
- Mean, Median, Mode
- Quartiles/Percentile
- Range, Variance, Standard Deviation, Co-efficient of Variation
- 68-95-99 Rule of SD
- Z Score (Standard Score)
- P-Value
- Maximum Likelihood Estimation
- Probability vs Likelihood
- PDF vs PMF
- Normal Distribution of Data
- Skewness & it’s types
- Kurtosis & it’s types
- Kth Central Moments
- Co-Variance/Joint Probability Distribution
- Correlation
- Entropy
- ANOVA
- Chi-Square
- F tests
- Types of Data Distribution
Real-time Practicals: Hands on- Lab using pen and paper Only
- Anaconda & Python
- Understanding Jupyter Notebooks
- Python Package Installation
- Tableau Installation
- Oracle Database & Server
- Concept of List, Data frame, Dictionary
- Connecting to Databases using Python
- Importing data from csv, text, Excel
- Converting JSON, XML, to Data frame
- Understanding EDA
- Frequency Distribution
- Analyzing NA, blanks
- Using SQL concepts inside Python
Real-time Practicals: Hands on- Lab using Python
- Handling missing Values
- Handling Outliers
- Normalization techniques
- Standardization techniques
- Regularization techniques
- Feature Extraction
- Train Test data selection
Real-time Practicals: Hands on- Lab using Python
- No Free Lunch
- Hypothesis vs Null Hypothesis
- BIAS VS Variance tradeoff
- Local Vs Global Minima/Maxima
- Bias – Loss/ Loss-Cost Function
- Understanding Regression math
- Linear Algebra concepts
- Least Mean Square
- Analyzing Co-relation
- Heat Maps, Pair Plots, Distribution Graphs
- Simple Vs Multiple Linear regression
- Train Test data selection
Real-time Practicals: Hands on- Lab & Model Implementation using Python
Impressed with our Course Content?
Attend a Free Demo Session to Experience our Quality!
Get Free Session - Understanding the math
- Polynomial Algebra concepts
- Degree of Polynomial
Real-time Practicals: Hands on- Lab & Model Implementation using Python
- Overfitting/ Under fitting/ Optimal Fits
- Handling Categorical Data inside
- Confusion Matrix
- Type I & Type II errors
- Precision Vs Accuracy
- AUC/ROC curve
- Understanding the statistics behind Logistic Sigmoid
- Logistic regression math
Real-time Practicals: Hands on- Lab & Model Implementation using Python
- Understanding the Decision Tree & Bagging
- Math behind Classification and Regression in tree
- Decision Tree concepts
- Using Random Forest for Regression
- K fold Cross Validation
- Model Optimizers
- Hyper parameter Tuning
Real-time Practicals: Hands on- Lab & Model Implementation using Python
- Understanding the Naïve Bayes theorem
- Bayesian Vs Gaussian theorems
- Using naïve Bayes for Regression
- Model Optimizers
- Hyper parameter Tuning
Real-time Practicals: Hands on- Lab & Model Implementation using Python
- Label Encoding
- One hot encoding
- Synonym treatment
- Stemming
- Lemmatization
- Stop words
- Parts Of Speech Tagging
- TF-IDF and its math Behind
Real-time Practicals: Hands on- Lab using Python
- Understanding the SVM Concept
- Hyper plane and Kernel
- Using SVM for Regression
- Grid Search
- Model Optimizers
- Hyper parameter Tuning
Real-time Practical: Hands on- Lab & Model Implementation using Python
- Understanding the Boosting Concept
- Hyper plane and Kernel
- Learning Rate
- Model Optimizers
- Hyper parameter Tuning
Real-time Practical: Hands on- Lab & Model Implementation using Python
- Understanding Nearest Neighbors concept
- Statistics behind K Means Clustering Algorithm
Real-time Practical: Hands on- Lab & Model Implementation using Python
- Understanding Deep learning
- MLP Vs other Deep Learning
- How Neural Network works & Architecture
- Activation functions.
- Model Optimizers
- Hyper parameter Tuning
- Best Practice and when to use DL
Real-time Practical: Hands on- Lab & Model Implementation using Python
- Introduction to H20.ai
- Pros and Cons
- Available models in H20.ai
Real-time Practical: Hands on- Lab & Model Implementation using Python
- Introduction to Sampling
- Over sampling and Under sampling
- SMOTE/SMOTENC & Near Miss
- Pros and Cons of sampling
- Introduction to DR
- PCA & it’s code
- Introduction to Pyinstaller
- Pickle and Joblib
Real-time Practical: Hands on- Lab & Model deployment using Python
- Introduction to Tableau
- Data sources
- Exploratory Data Analysis
- Clustering Analysis and Inferences using Tableau
- Creating visualizations
Real-time Practical: Hands on- Lab using Tableau
You will be going through detailed 2 to 3 months of Data Science Hands-on training
- Detailed instructor led sessions to help you become a proficient Expert in Data Science.
- Build a Data Science professional portfolio by working on hands on assignments and projects.
- Personalised mentorship from professionals working in leading companies.
- Lifetime access to downloadable Data Science course materials, interview questions and project resources.
Credo Systemz - Velachery, Chennai
Call Us +91 9884412301
Credo Systemz - OMR, Chennai
Call Us +91 9600112302
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Hi, here I have attended Data Science training in Credo Systemz. I have improved my Data Science knowledge from the basic level. I really appreciate this Institute for doing such a great and better job. In every training session, I got new information about Data Science. My trainer also helped me clear interviews easily. I have referred many students in Credo for do all training.
I am Gowri and I am very glad about my Data Science training provided by Credo Systemz software training institute. Trainer explains every concept with real time examples and use cases so easy to understand every concept. My trainer way of the teaching is good. It's a best software training institute for software courses. Thank you, Credo Systemz and my trainer...
Hello everyone this is Durga from chrompet, I joined Credo Systemz for my data science training course in JAN month. I have nearly 4+ years of experience as a python developer and also having some work experience in handling data. So I like to do Data Science course, and one of my friend referred me Credo Systemz. I had attended demo session at first with the trainer, he gave a complete overview about the course which impressed me and make me to join for the course. The session went extremely well, can able to learn my real time scenarios because of the experience of the trainer. Data Science course fees also worth for this training. Now I am confident enough that I have all the skills required to be a Professional Data Scientist.
Hai, This is Radha and recently completed my Data science training in Chennai at Credo Systemz. I’m really impressed with Data science Course topics so I enrolled here. During the class, my trainer give more use cases which help us to understand the Data science concepts easily and Approaching way of a trainer in Subject is good and crystal clear, Trainer would be available through WhatsApp if we have any clarifications. I’ll recommend credo systemz is the best data science training in chennai those who are looking to start data science as their career.
