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— pantech elearning —
Advance Certification Program
MATLAB for image
Carrier-Based Complete Data Science Training: Algorithms, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning
45 Hours Total Length
Starts On May, 26th
Lifetime Access
everything you need to
Become a Successful Interface Designer
13+ Core Conepts
30+ Projects
Live / Recorded
Lifetime Access
Community Suported
PPTS & Downloadables
Becoming an Interface Designer
Step by Step
Step by Step Learning Process
Pre-Process & Understanding Data
Data Preparation
- ✓ Perform OOPS Concepts in Python
- ✓ Carry out cluster and factor analysis
- ✓ Be able to understand Machine Learning algorithms in Python, using NumPy, stats models, and sci-kit-learn
- ✓ Apply your skills to real-life cases & examples
Data Processing
- ✓ The course provides the entire Knowledge you need to become a data scientist
- ✓ Fill up your resume with in-demand data science tools & skills: Statistical analysis,
- Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep Learning with TensorFlow
- ✓ Learn how to pre-process data Understand the mathematics behind Machine Learning
- ✓ Start coding in Python and learn how to use it for statistical analysis
Data Execution
- ✓ Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlow & Keras
- ✓ Develop a Model while coding and solving tasks with Algorithms
- ✓ Unfold the power of deep neural networks
- ✓ Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross-validation, testing, and how hyperparameters could improve performance
- ✓ Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
Carrier Based Learning Process
Course Curriculum (45 Hrs)
- Python Basics
- Python Data Structures
- Python Fundamentals
- Advance Python (oops)
- Pandas for Data Science
- NumPy for Data Science
- Matplotlib
- Seaborn
- Scikit-Learn
- NLTK
- Keras
- Tableau – Data visualization
- Tableau – Data Sources, Worksheet
- Introduction power BI
- Visualize Data in the Form of Various Charts, Plots, and Maps BI tools – Power BI
- Google Colab Notebook
- Python – Date and Time, Data Wrangling
- Python – Data Aggregation
- Python – Word Tokenization, Stemming, and Lemmatization
- Python – Data Visualization
- Python – Statistical Analysis
- Python – Types Of Distribution
- Python – Correlation, Chi-Square Test, Linear Regression
- Supervised Learning – Classification and Regression
- Liver disease Prediction – (Logistic Regression)
- Crime Analysis – (KNN Algorithm)
- Classifying muffins and cupcakes – (SVM Algorithm)
- Fake news detection – (Naïve Baye’s)
- Android malware – (Decision tree)
- Credit card Fraud detection – (Random Forest)
- Evaluating the classification model – (Confusion matrix) Calculating the accuracy score.
- Classification model selection For Breast Cancer – (Classification)
- Employee Salary Prediction – (Linear Regression Single Variable)
- Advertisement and Sales Prediction – (Multiple Linear Regression)
- Generating Data points based on some equation – (Polynomial Regression)
- Ice – Cream shop revenue prediction from temperature – (Decision Tree Regression)
- Agriculture Price Prediction – (Random Forest Algorithm)
- Evaluating the performance of my regression model – ( Root mean square error and R2 score)
- Regression Model selection for sales forecasting.
- Unsupervised Learning – Clustering
- Crime Pattern Analysis – (K-Means Clustering)
- Customer Spending Analysis – (Hierarchical Clustering)
- Flower Species – Data Visualization
- Image Compression Using – SVD (Singular Value Decomposition)
- Unsupervised Learning – Association
- Market Basket Analysis – (APRIARI)
- Market Basket Optimization / Analysis – (ECLAT)
- Reinforcement Learning
- Web Ads click-through rate optimization – (Upper Bound Confidence)
- Natural Language Processing
- Hate Speech Detection – (NLTK)
- Loan Prediction Problem – (XGBoost)
- Deep Learning
- Movie Review Classification – (RNN)
- Digits Classification – (CNN)
- AI – Cart Pole (Reinforcement Learning)
Want to Become a
Data Analysit?
The course provides the entire Knowledge you need to become a data scientist Fill up your resume with in-demand data science tools & skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and sci-kit-learn, Deep Learning with TensorFlow
Learn from our graduates
Benefits of Learning Course
> Essential Python concepts for data science, including data types, variables, loops, and functions
> How to work with data using Python’s powerful data manipulation libraries, such as NumPy and Pandas
> How to visualize data using Python libraries such as Matplotlib and Seaborn
> How to visualize data using tools such as Tableau and Power bi
> Machine learning with Python: Supervised, Unsupervised Reinforcement Learning
> Techniques and best practices for effective data analysis and data storytelling
Learn from our graduates
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Learn from our graduates
Certification
Meet your Mentor
pilip Bedit
The course provides the entire Knowledge you need to become a data scientist Fill up your resume with in-demand data science tools & skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and sci-kit-learn, Deep Learning with TensorFlow
It’s Time to
Grab the Discount!
- 13 + Core Concepts (45 Hours total)
- Available from May, 26th
- Lifetime Access
- 1 Hrs Weekly Mentor Sessions
- Language: English
- Live Sessions with Mentor
Why Bold Academy?
Frequently Asked Questions
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